Small-scale Turbulent Structures Research Articles

LES-based validation of a dynamic wind farm flow model under unsteady inflow and yaw misalignment

This work presents the validation of an extended version of the control-oriented, dynamic wind farm flow solver SPLINTER. The two-dimensional model is applied to use cases of wake steering by yaw misalignment and inflow wind direction variations and the results are compared to large-eddy simulations (LES). While SPLINTER is able to reproduce the antagonal behaviour of decreasing upstream and increasing downstream turbine power under wake deflection, a systematic deviation of the downstream power is detected and quantified, which is connected to underrepresented three-dimensional wake effects. In case of changing inflow wind direction, SPLINTER is capable of computing movement and shape of the bending wakes. The model smooths small-scale turbulent structures and disturbances and does not reproduce wake meandering, but manages to describe the evolution of the mean flow, which is tested by averaging over an ensemble of LES and comparing the resulting flow fields and turbine power time series. Under dynamic inflow conditions, SPLINTER is able to predict at which time intervals and at which rates downstream turbines will be influenced by wakes, which can improve the accuracy of short-term power and load forecasting and enables its application to online model predictive wind farm control.

Improving virtual heat transfer description of developed and undeveloped annular gap flows at high Taylor numbers

Increased power densities of electric machines are, amongst other factors, related also to the increase of the rotors’ rotating velocities. These can be combined with axial flow to improve the heat transfer in the annular gap. The resulting high rotating and axial velocities are characterized with high Taylor (Ta) and Reynolds (Re) numbers. Such flow regimes are currently not yet thoroughly described. The reasons are in the complex interactions between the operating conditions, annular gap geometry and the conditions at the gap inlet, which affect the flow development in the gap. Each of these impacts varies between different electric machines, adding to the complexity of description. To address this, a numerical study based on 3D CFD simulations is performed. The study accounts for the impacts of the flow conditioning at the entrance to the annular gap and the possibility that the small scale turbulent structures might not be well resolved at high Ta numbers. Thus, different inflow configurations are applied using both RANS and LES models. The results are compared with available experimental and numerical data and provide a valuable insight into the requirements for reliable heat transfer description in the increasingly interesting flow conditions.

Turbulent flow around submerged foundation arrays for ocean energy

Submerged ocean energy foundations experience dynamic loading due to the non-uniform approach velocity and wake propagation behind them. This paper investigates the unsteady turbulent flow dynamics and propagation of large-scale vortical structures around submerged foundations using a large eddy simulation. The computational domain constituted an array of eight foundations arranged in an inline configuration of two columns. Two streamwise spacing, x = 6D and 8D, are investigated at an approach Reynolds number, based on the channel hydraulic diameter, of 8.5 × 104. The parametric study reveals the expected changes in wake recovery and their impact on the downstream foundations. The narrow spacing promotes intense wake interactions, while larger inline spacing causes the entrainment of ambient flow, thereby limiting the wake interaction with the downstream foundations. A two-point correlation analysis reveals larger integral turbulent timescales for the 6D spacing compared to the 8D spacing. The separated flow around the foundations is characterized by eddies shed at varying frequencies. Multiple spectra peaks dominate at low frequencies, signifying dominant energy-containing large-scale vortices coupled with periodic excitation of the vortices as energy is transferred from the large-to small-scale turbulent structures.

Tip Vortex Study of a Rotor with Double-Swept Blade Tips

An experimental aerodynamic study was conducted, analyzing the wake structure of a four-bladed model rotor with a forward-backward swept tip geometry inspired by the ONERA-DLR “Etude d´un Rotor Aéroacoustique Technologiquement Optimisé”-design. Similar tip designs are used on some modern helicopter main rotors. The experiments were conducted at the Rotor Test Facility Göttingen (RTG) in hover-like conditions using a stereoscopic high-speed particle image velocimetry system. The results are compared with those of a reference rotor using a conventional parabolic blade tip. The test parameters include both constant-pitch cases and pitch-oscillating cases with a cyclic swashplate input. The constant-pitch tests show a two-step stall behavior for the double-swept tip, with the first step characterized by a reduced thrust slope and a reduced rotor efficiency. This effect is explained by a repositioning and a structural change of the tip vortex generation. The pitch-oscillating cases show that the double-swept tip results in an earlier tip stall compared to the parabolic geometry while maintaining high thrust levels. The dynamic tip stall yields a break-down of the wake’s tip vortex system, which is replaced by a spanwise band with small-scale turbulent structures and trailed vorticity, but no large-scale vortices.

Four-dimensional variational data assimilation of a turbulent jet for super-temporal-resolution reconstruction

The super-temporal-resolution (STR) reconstruction of turbulent flows is an important data augmentation application for increasing the data reach in measurement techniques and understanding turbulence dynamics. This paper proposes a data assimilation (DA) strategy based on weak-constraint four-dimensional variation to conduct an STR reconstruction in a turbulent jet beyond the Nyquist limit from given low-sampling-rate observations. Highly resolved large-eddy simulation (LES) data are used to produce synthetic measurements, which are used as observations and for validation. A segregated assimilation procedure is realised to assimilate the initial condition, inflow boundary condition and model error separately. Different types of observational data are tested. The first type is down-sampled LES data containing many small-scale turbulence structures with or without synthetic noise. The DA results show that the temporal variation of the small-scale structures is well recovered even with noise in the observations. The spectra are resolved to a frequency approximately one order of magnitude higher than what can be captured within the Nyquist limit. The second type of observation is low-sampling-rate tomographic particle image velocimetry (tomo-PIV) data with or without the injection of small-scale structures. The modulation between the large-scale structures contained in the tomo-PIV fields and the small scales injected from the observations is improved. The resultant small scales in the STR reconstruction have the characteristics of authentic turbulence to a considerable extent. Additionally, DA yields much smaller errors in the prediction of particle positions when compared with the Wiener filter, demonstrating the great potential for Lagrangian particle tracking in measurement techniques.

Estimation of Astronomical Seeing with Neural Networks at the Maidanak Observatory

In the present article, we study the possibilities of machine learning for the estimation of seeing at the Maidanak Astronomical Observatory (38∘40′24″ N, 66∘53′47″ E) using only Era-5 reanalysis data. Seeing is usually associated with the integral of the turbulence strength Cn2(z) over the height z. Based on the seeing measurements accumulated over 13 years, we created ensemble models of multi-layer neural networks under the machine learning framework, including training and validation. For the first time in the world, we have simulated optical turbulence (seeing variations) during night-time with deep neural networks trained on a 13-year database of astronomical seeing. A set of neural networks for simulations of night-time seeing variations was obtained. For these neural networks, the linear correlation coefficient ranges from 0.48 to 0.68. We show that modeled seeing with neural networks is well-described through meteorological parameters, which include wind-speed components, air temperature, humidity, and turbulent surface stresses. One of the fundamental new results is that the structure of small-scale (optical) turbulence over the Maidanak Astronomical Observatory does not depend or depends negligibly on the large-scale vortex component of atmospheric flows.

Numerical simulation of the equatorial plasma bubble: the effect of seeding by the vertical winds and random background noise perturbations

A wide variety of small-amplitude waves widely exist in the ionosphere and have significant effects on the evolution of equatorial plasma bubbles. In this paper, we simulated equatorial plasma bubbles (EPB) seeded by vertical neutral wind perturbations with wavelengths of 125 km and 250 km, and compared the morphology characteristics of plasma bubble structures with those under random noise perturbations in the background density. The numerical results showed that both vertical winds and random background noise perturbations can contribute to the growth of plasma bubbles, and the perturbations under additional random background noise can promote the growth of the plasma bubble structures faster. Additionally, several processes of the nonlinear behavior of bifurcated EPB structures, including bifurcation, pinching, and small-scale turbulent structures, were successfully obtained. Our simulation captured supersonic flows within the low-density plasma structures characterized by vertical velocities of about 1.5 km/s, which is consistent with experimental studies found in the literature.

Numerical investigation on the rotor-turbulence interaction noise

Noise from a turbomachinery component, such as compressors and turbines, is an important issue to be resolved in aerospace and ocean engineering applications. The rotor of a turbomachinery assembly usually could operate downstream to other flow structures (fuselages, stators, control surfaces, etc.) that produce either large-scale or small-scale turbulence structures, which are highly complex and are being distorted while they are ingested into the rotor, which generate the rotor-turbulence interaction noise. The presented work conducted numerical simulation research on a ten-bladed rotor ingesting different turbulence structures. The large eddy simulation (LES) and Ffowcs-Williams and Hawkings (FW-H) methods were used to predict the flow-induced noise from the rotor. The results show that the time-space evolution of the upstream turbulent structure when it passes towards the rotor. In addition, the differences in the turbulence ingestion noise at different inflow speeds and rotational speeds were studied. Furthermore, the sound generation mechanism of turbulent ingestion noise was explored using a newly proposed near-field sound source analysis method. In summary, this study can help to improve the understanding of the physical mechanisms of unsteady forces and noise generated by a rotor when it interacts with ingesting turbulent flows.

Fluid Simulation over a Rotating Disk: Momentum and Mass Transfer across the Wafer Boundary

This research focuses on the crucial task of identifying the viscous sublayer in improving wet cleaning processes. Computational fluid dynamics (CFD) is employed to manipulate fluid properties and process parameters for optimizing cleaning efficiency. The research findings encompass the evolution of thickness across the wafer radius, characterization of the wavy air-liquid interface, velocity profile within the liquid, and measurement of the viscous sublayer's thickness. Key findings highlight the significance of small-scale turbulent structures, the competition between Coriolis and viscous forces, and the successful utilization of CFD LES (Large Eddy Simulation) for quantifying and visualizing the viscous sublayer and eddy flow.

Quantitative Prediction of Sling Events in Turbulence at High Reynolds Numbers.

Collisional growth of droplets, such as occurring in warm clouds, is known to be significantly enhanced by turbulence. Whether particles collide depends on their flow history, in particular on their encounters with highly intermittent small-scale turbulent structures, which despite their rarity can dominate the overall collision rate. Here, we develop a quantitative criterion for sling events based on the velocity gradient history along particle paths. We show by a combination of theory and simulations that the problem reduces to a one-dimensional localization problem as encountered in condensed matter physics. The reduction demonstrates that the creation of slings is controlled by the minimal real eigenvalue of the velocity gradient tensor. We use fully resolved turbulence simulations to confirm our predictions and study their Stokes and Reynolds number dependence. We also discuss extrapolations to the parameter range relevant for typical cloud droplets, showing that sling events at high Reynolds numbers are enhanced by an order of magnitude for small Stokes numbers. Thus, intermittency could be a significant ingredient in the collisional growth of rain droplets.

Similarity of length scales in high-Reynolds-number wall-bounded flows

The wall dependence of length scales used to describe large- and small-scale structures of turbulence is examined using highly resolved experiments in zero-pressure-gradient turbulent boundary layers and pipe flows spanning the range $2000< Re_\tau <37\ 700$ . Of particular interest is the influence of external intermittency on the scaling of these length scales. It is found that when suitable scaling parameters are selected and external intermittency is accounted for, the dissipative motions follow inner scaling even into the outer-scaled regions of the flow, and that certain large-scale descriptions follow outer scaling even in the inner-scaled regions of the flow. The wall dependence is the same for both internal pipe and external boundary layer flows, and the different length scales can be related to recognizable features in the longitudinal wavenumber spectrum.

Influence of optical aperture sizes on aero-optical effects induced by supersonic turbulent boundary layers.

With the increase of flight speed, aero-optical effects induced by the turbulent boundary layer near the optical window become increasingly significant. The density field of the supersonic (Mach 3.0) turbulent boundary layer (SPTBL) was measured by nano-tracer-based planar laser scattering technique, and the optical path difference (OPD) was obtained through ray-tracing method. The influence of the optical aperture size on the aero-optical effects of SPTBL was studied in detail, and the underlying mechanisms were analyzed from the perspective of the turbulent structure scales. The influence of the optical aperture on the aero-optical effects is mainly due to turbulent structures with different scales. The beam center jitter (s x¯) and offset (x¯) are mainly caused by turbulent structures larger than the optical aperture size, while the beam spread about the center (x ' 2¯) is mainly caused by turbulent structures smaller than the optical aperture size. With the increase of optical aperture size, the proportion of turbulent structures larger than the optical aperture size decreases, which can suppress the beam jitter and the beam offset. Meanwhile, since the beam spread is primarily induced by small-scale turbulent structures with relatively strong density fluctuation intensity, the spread increases rapidly to its peak and then gradually stabilizes as the optical aperture size grows.

Coherent structures at the origin of time irreversibility in wall turbulence

Time irreversibility is a distinctive feature of non-equilibrium phenomena such as turbulent flows, where irreversibility is mainly associated with an energy cascade process. The connection between time irreversibility and coherent motions in wall turbulence, however, has not been investigated yet. An Eulerian, multiscale analysis of time irreversibility in wall-bounded turbulence is proposed in this study, which differs from previous works relying on a Lagrangian approach and mainly focusing on homogeneous turbulence. Outcomes reveal a strong connection between irreversibility levels and coherent structures in both turbulent channel and boundary layer flows. In the near-wall region, irreversibility is directly related to the inner spectral peak originating from small-scale turbulent structures in the buffer layer. Conversely, stronger irreversibility is found in correspondence to the outer spectral peak originating from larger turbulent flow scales far from the wall. Our results represent a first effort to characterize Eulerian TI in wall-bounded turbulent flows, thus paving the way for further developments in wall-turbulence modeling and control accounting for broken temporal symmetry.

Airborne Quantum Key Distribution Performance Analysis under Supersonic Boundary Layer.

Airborne quantum key distribution (QKD) that can synergize with terrestrial networks and quantum satellite nodes is expected to provide flexible and relay links for the large-scale integrated communication network. However, the photon transmission rate would be randomly reduced, owing to the random distributed boundary layer that surrounding to the surface of the aircraft when the flight speed larger than Mach 0.3. Here, we investigate the airborne QKD performance with the BL effects. Furthermore, we take experimental data of supersonic BL into the model and compare the airborne QKD performance under different conditions. Simulation results show that, owing to the complex small-scale turbulence structures in the supersonic boundary layer, the deflection angle and correspondingly drifted offset of the beam varied obviously and randomly, and the distribution probability of photons are redistributed. And the subsonic and supersonic boundary layer would decrease ~35.8% and ~62.5% of the secure key rate respectively. Our work provides a theoretical guidance towards a possible realization of high-speed airborne QKD.

Heat transfer characteristics of jet impingement on a surface mounted with ribs using LES

The present study investigates flow and heat transfer features of jet impingement on a surface fitted with detached ribs at Re = 20,000 using OpenFOAM 4.1 based large eddy simulation (LES). The WALE SGS model is applied. A wall resolved simulation is performed to understand the flow behaviour and heat transfer enhancement in the impingement regions and ribs. The WALE model is observed to be suitable for accurate calculations of complex application-based flow configurations. A comprehensive discussion on flow physics is carried out to understand heat transfer in the rib regions and the effects of flow and turbulence parameters. The investigation reveals that augmentations in the velocity and turbulence are directly linked to the local heat transfer enhancement in the clearance between the ribs and heated plate. A dual peak exists for turbulence kinetic energy profiles. The local heat transfer is observed to be maximum in the clearance region between the second rib and plate. The region of maximum local heat transfer was observed to be related to the peak velocity and turbulence kinetic energy in the same region. The present computation is capable of capturing small-scale dynamics and turbulence structures. The present results may be utilized in testing RANS-based turbulence models and the findings are useful for researchers and engineers working on EV, HPC and related cooling industries where high localized cooling is required.

Turbulence structures and entrainment length scales in large offshore wind farms

Abstract. The flow inside and around large offshore wind farms can range from smaller structures associated with the mechanical turbulence generated by wind turbines to larger structures indicative of the mesoscale flow. In this study, we explore the variation in turbulence structures and dominant scales of vertical entrainment above large offshore wind farms located in the North Sea, using data obtained from a research aircraft. The aircraft was flown upstream, downstream, and above wind farm clusters. Under neutrally stratified conditions, there is high ambient turbulence in the atmosphere and an elevated energy dissipation rate compared to stable conditions. The intensity of small-scale turbulence structures is increased above and downstream of the wind farm, and it prevails over mesoscale fluctuations. But in stable stratification, mesoscale flow structures are not only dominant upstream of the wind farm but also downstream. We observed that the vertical flux of horizontal momentum is the main source of energy recovery in large offshore wind farms, and it strongly depends on the magnitude of the length scales of the vertical wind velocity component. The dominant length scales of entrainment range from 20 to ∼60 m above the wind farm in all stratification strengths, and in the wake flow these scales range from 10 to ∼100 m only under near-neutral stratification. For strongly stable conditions, negligible vertical entrainment of momentum was observed even just 2 km downstream of large wind farms. We also observed that there is a significant lateral momentum flux above the offshore wind farms, especially under strongly stable conditions, which suggests that these wind farms do not satisfy the conditions of an “infinite wind farm”.

Thermal-fluctuation effects on small-scale statistics in turbulent gas flow

Kolmogorov's theory of turbulence assumes that the small-scale turbulent structures in the energy cascade are universal and are determined by the energy dissipation rate and the kinematic viscosity alone. However, thermal fluctuations, absent from the continuum description, terminate the energy cascade near the Kolmogorov length scale. Here, we propose a simple superposition model to account for the effects of thermal fluctuations on small-scale turbulence statistics. For compressible Taylor–Green vortex flow, we demonstrate that the superposition model in conjunction with data from direct numerical simulation of the Navier–Stokes equations yields spectra and structure functions that agree with the corresponding quantities computed from the direct simulation Monte Carlo method of molecular gas dynamics, verifying the importance of thermal fluctuations in the dissipation range.

WMLES of flows around small-scale propellers - estimating aerodynamic performance and wake visualization

Wall-modeled large-eddy simulation (WMLES) is an advanced mathematical model for turbulent flows which solves for the low-pass filtered numerical solution. A subgrid-scale (SGS) model is used to account for the effects of unresolved small-scale turbulent structures on the resolved scales (i.e. for the dissipation of the smaller scales), while the flow behavior near the walls is modeled by wall functions (thus reducing the requirements for mesh fineness/ quality). This paper investigates the possibilities of applying WMLES in the estimation of aerodynamic performance of small-scale propellers, as well as in the analysis of the wake forming downstream. Induced flows around two propellers designed for unmanned air vehicles (approximately 25 cm and 75 cm in diameter) in hover are considered unsteady and turbulent (incompressible or compressible, respectively). Difficulties in computing such flows mainly originate from the relatively low values of Reynolds numbers (several tens to several hundreds of thousands) when transition and other flow phenomena may be present. The choice of the employed numerical model is substantiated by comparisons of resulting numerical with available experimental data. Whereas global quantities, such as thrust and power (coefficients), can be predicted with satisfactory accuracy (up-to several percents), distinguishing the predominant flow features remains challenging (and requires additional computational effort). Here, wakes forming aft of the propeller rotors are visualized and analyzed. These two benchmark examples provide useful guidelines for further numerical and experimental studies of small-scale propellers.

Applications of wide-ranging PIV measurements for various turbulent statistics in artificial atmospheric turbulent flow in a wind tunnel

Particle image velocimetry (PIV) is currently the only method which can experimentally quantify the spatial distributions of velocity with high sampling frequencies without causing intrusions into the airflow of the measuring devices. To extend the use of PIV systems for determining the distributions of velocity for wind environmental and engineering purposes, this study showed various applications of wide-ranging PIV systems for an artificially created turbulent flow at the wind-tunnel scale. Various turbulent statistics, which are commonly employed for evaluating the wind structures and environments, were compared among three conditions of the measurement areas covered by PIV systems and a hot-wire anemometry (HWA). The largest measurement covering 500 × 500 mm2 can capture the turbulent motions extending to 40% of the entire boundary layer. In addition, the discrepancies on two-length scales could be discussed using spatial and temporal correlation functions owing to the wide-ranging PIV. Moreover, the limitations of the wide-ranging PIV systems were clarified. While the turbulent statistics compared among three PIV conditions and HWA demonstrated adequate agreement, the PIV with the largest measurement area failed to capture the small-scale turbulent structures due to the coarse grid resolutions. Moreover, the measurement resolutions of PIV systems demonstrated sensitivity in determining the spectrum and probability density functions, whereas a wide-ranging PIV system can cover wide-ranging measurement areas.

Machine Learning Based Developing Flow Control Technique Over Circular Cylinders

Abstract This paper demonstrates the feasibility of blowing and suction for flow control based on the computational fluid dynamics (CFD) simulations at a low Reynolds number flows. The effects of blowing and suction position, and the blowing and suction mass flowrate, and on the flow control are presented in this paper. The optimal conditions for suppressing the wake of the cylinder are investigated by examining the flow separation and the near wake region; analyzing the aerodynamic force (lift and drag) fluctuations using the fast Fourier transform (FFT) to separate the effects of small-scale turbulent structures in the wake region. A method for stochastic analysis using machine learning techniques is proposed. Three different novel machine learning methods were applied to CFD results to predict the variation in drag coefficient due to the vortex shedding. Although, the prediction power of all the methods utilized is in the acceptable accuracy range, the Gaussian process regression (GPR) method is more accurate with an R2(coefficient of determination) > 0.95. The results indicate that by optimizing the blowing and suction parameters like mass flowrate, slot location, and the slot configuration, up to 20% reduction can be achieved in the drag coefficient.