Numerical Analysis of the Influence of Turbulence Intensity on Iced Conductors Gallop Phenomena

Turbulence is expected to play a relevant role in the so-called conductor gallop phenomena,namely,the high-amplitude,low-frequency oscillation of overhead power lines due to the formation of ice structures and the ensu-ing effect that wind can have on these.In this work,the galloping time history of a wire with distorted(fixed in time)shape due to the formation of ice is analyzed numerically in the frame of afluid-solid coupling method for different wind speeds and levels of turbulence.The results show that the turbulence intensity has a moderate effect on the increase of the conductor’s aerodynamic lift and drag coefficients due to ice accretion;nevertheless,the corresponding changes in the torsion coefficient are very significant and complicated.A high turbulence intensity can affect the torsion coefficient in a certain range of attack angles and increase the torsion angle of the conductor.Through comparison of the galloping phenomena for different wind velocities,it is found that the related amplitude grows significantly with an increase of the wind speed.For a relatively large wind speed,the galloping amplitude is more sensitive to the turbulence intensity.Moreover,the larger the turbulence intensity,the larger the conductor’s vertical and horizontal galloping amplitudes after icing.The torsion angle also increases with an increase in the wind speed and turbulence intensity.

Effect of turbulence intensity on airfoil flow:numerical simulations and experimental measurements

The effect of the turbulence intensity of the oncoming stream on the aerodynamic characteristics of the NACA-0012 airfoil is investigated by a direct numerical simulation. The numerical results are found to be consistent with the experimental measurements. Based on the finite spectral QUICK scheme, the simulation gets the high accuracy results. Both the simulation and the experiment reveal that the airfoil stall does not exist for the low turbulence intensity, however, occurs when the turbulence intensity increases sufficiently. Besides, the turbulence intensity has a significant effect on both the airfoil boundary layer and the separated shear layer.

Influence of Turbulence Intensity and Turbulence Length Scale on the Drag, Lift and Heat Transfer of A Circular Cylinder

Influence of the turbulence intensity and turbulence length scale on the hydrodynamic characteristics and heat transfer of a circular cylinder, streamlined by a viscous fluid flow, is numerically studied. We take the Reynolds number of the oncoming flow equal to 4×10^4, the turbulence intensity Tuf and the dimensionless turbulence length scale L-f varying from 1.0% to 40% and from 0.25 to 4.0, respectively. We confirmed that the increase of Tuf leads to the suppression of the periodic vortex shedding from the cylinder surface, and as a result the stationary mode of streamlining is formed. Consequently, with the increasing turbulence intensity directly in front of the cylinder Tu＊, the amplitude of the lift coefficient decreases monotonically. Nevertheless, the time-averaged drag coefficient of the streamlined cylinder decreases at Tu＊〈6.0%, and increases at Tu＊〉9.0%. The dependence of the average Nusselt number on Tu＊ is near-linear, and with the increasing turbulence intensity, the Nusselt number rises. However, the change of the average Nusselt number depending on L-f is non-monotonic and at Lf=l.0, the value reaches its maximum

Updating empirical results of wind loads on cooling towers for turbulence intensity effects

Variations of wind effects on large cooling towers observed at different turbulence intensities for our previous full-scale measurements might be caused by the inherent uncertainties in our physical experiments.Accordingly,the one-way analysis of variance(ANOVA)technique is employed for analyzing the data measured on the prototype Pengcheng cooling tower.Because ANOVA indicates that the variations of full-scale wind effects are basically the effects of turbulence intensity,the empirical results of wind loads on cooling towers obtained by generalizing physical experimental data without considering the turbulence intensity effects are updated using model test results obtained in multiple flow fields.The empirical fluctuating wind pressure distribution is updated based on the fact that the fluctuating wind pressure coefficient linearly increases with the increase in the turbulence intensity,and the empirical formulae of the spectra and the coherences is updated based on conservative assumptions.Comparisons of the empirical results and full-scale measurement data suggest that the original empirical results are either too conservative or unsafe for use.However,economic efficiency and conservativeness will be balanced if the updated empirical results are employed for the wind engineering design.

Experimental Investigation of Flow Drag and Turbulence Intensity of a Channel Flow with Rough Walls

Turbulent flow over rough walls is investigated through acoustic doppler velocimeter measurements.Smooth rods with a diameter of 6 mm are used as roughness elements.The rods are arranged at the channel bottom wall in three ways:longitudinally(along the flow direction);transversely(orthogonally to flow direction);and mesh-shaped(in a staggered mesh).The transverse roughness elements produce higher disturbance and flow drag than longitudinal roughness.Both turbulence intensity and flow drag for mesh-shaped roughness are not significantly different from those of transverse roughness,indicating that the transverse roughness elements mainly affect turbulence characteristics.Both turbulence intensity and flow drag are greatest for transverse rough walls at w/k=7;likewise,both increase with decreasing w/k for longitudinal rough walls.Compared with channel flow over a smooth wall,the turbulence intensity increases considerably,while the flow drag only increases slightly when w/k is small for the three arrangements.This is beneficial for enhancing heat transfer and mixing in channel flows with relatively small flow resistance.

The Effects of Turbulence Intensity and Tip Speed Ratio on the Coherent Structure of Horizontal-Axis Wind Turbine Wake:A Wind Tunnel Experiment

The evolution laws of the large-eddy coherent structure of the wind turbine wake have been evaluated via wind tunnel experiments under uniform and turbulent inflow conditions.The spatial correlation coefficients,the turbulence integral scales and power spectrum are obtained at different tip speed ratios(TSRs)based on the time-resolved particle image velocity(TR-PIV)technique.The results indicate that the large-eddy coherent structures are more likely to dissipate with an increase in turbulence intensity and TSR.Furthermore,the spatial correlation of the longitudinal pulsation velocity is greater than its axial counterpart,resulting into a wake turbulence dominated by the longitudinal pulsation.With an increase of turbulence intensity,the integral scale of the axial turbulence increases,meanwhile,its longitudinal counterpart decreases.Owing to an increase in TSR,the integral scale of axial turbulence decreases,whereas,that of the longitudinal turbulence increases.By analyzing the wake power spectrum,it is found that the turbulent pulsation kinetic energy of the wake structure is mainly concentrated in the low-frequency vortex region.The dissipation rate of turbulent kinetic energy increases with an increase of turbulence intensity and the turbulence is transported and dissipated on a smaller scale vortex,thus promoting the recovery of wake.

Baseline design of the KunLun Turbulence Profiler instrument

Adaptive optics systems are the most powerful tools to counteract the image blurring caused by atmospheric turbulence,allowing ground-based telescopes to capture high-resolution images.A critical parameter influencing adaptive optics system performance is the atmospheric refractive index structure constant,C_(n)^(2),which characterizes the intensity of atmospheric optical turbulence as a function of altitude.Given its simplicity,the lunar scintillometer is the preferred method for detecting atmospheric turbulence in challenging environments like Dome A in Antarctica,where sites are still in the developmental stages and local environmental conditions are extremely harsh.However,optimizing the performance of such instruments requires carefully determining the baseline configuration of photon sensors according to each site's specific optical turbulence profile characteristics.This study uses a Monte Carlo method to identify the optimal configuration for the KunLun Turbulence Profiler(KLTP),an instrument comparable to the lunar scintillometer,developed for use at Dome A.Simulations conducted using the obtained optimal baseline configuration recovered three different model optical turbulence profiles,demonstrating the effectiveness of our method in obtaining an optimal baseline configuration.Our approach can be easily applied to baseline design for similar turbulence profilers at other sites.

Properties of focused Laguerre–Gaussian beam propagating in anisotropic ocean turbulence

We analyze the properties of a focused Laguerre–Gaussian(LG)beam propagating through anisotropic ocean turbulence based on the Huygens–Fresnel principle.Under the Rytov approximation theory,we derive the analytical formula of the channel capacity of the focused LG beam in the anisotropic ocean turbulence,and analyze the relationship between the capacity and the light source parameters as well as the turbulent ocean parameters.It is found that the focusing mirror can greatly enhance the channel capacity of the system at the geometric focal plane in oceanic turbulence.The results also demonstrate that the communication link can obtain high channel capacity by adopting longer beam wavelength,greater initial beam waist radius,and larger number of transmission channels.Further,the capacity of the system increases with the decrease of the mean squared temperature dissipation rate,temperature-salinity contribution ratio and turbulence outer scale factor,and with the increase of the kinetic energy dissipation rate per unit mass of fluid,turbulence inner scale factor and anisotropy factor.Compared to a Hankel–Bessel beam with diffraction-free characteristics and unfocused LG beam,the focused LG beam shows superior anti-turbulence interference properties,which provide a theoretical reference for research and development of underwater optical communication links using focused LG beams.

Detection of Turbulence Anomalies Using a Symbolic Classifier Algorithm in Airborne Quick Access Record(QAR)Data Analysis

As the risks associated with air turbulence are intensified by climate change and the growth of the aviation industry,it has become imperative to monitor and mitigate these threats to ensure civil aviation safety.The eddy dissipation rate(EDR)has been established as the standard metric for quantifying turbulence in civil aviation.This study aims to explore a universally applicable symbolic classification approach based on genetic programming to detect turbulence anomalies using quick access recorder(QAR)data.The detection of atmospheric turbulence is approached as an anomaly detection problem.Comparative evaluations demonstrate that this approach performs on par with direct EDR calculation methods in identifying turbulence events.Moreover,comparisons with alternative machine learning techniques indicate that the proposed technique is the optimal methodology currently available.In summary,the use of symbolic classification via genetic programming enables accurate turbulence detection from QAR data,comparable to that with established EDR approaches and surpassing that achieved with machine learning algorithms.This finding highlights the potential of integrating symbolic classifiers into turbulence monitoring systems to enhance civil aviation safety amidst rising environmental and operational hazards.

Mapping Network-Coordinated Stacked Gated Recurrent Units for Turbulence Prediction

Accurately predicting fluid forces acting on the sur-face of a structure is crucial in engineering design.However,this task becomes particularly challenging in turbulent flow,due to the complex and irregular changes in the flow field.In this study,we propose a novel deep learning method,named mapping net-work-coordinated stacked gated recurrent units(MSU),for pre-dicting pressure on a circular cylinder from velocity data.Specifi-cally,our coordinated learning strategy is designed to extract the most critical velocity point for prediction,a process that has not been explored before.In our experiments,MSU extracts one point from a velocity field containing 121 points and utilizes this point to accurately predict 100 pressure points on the cylinder.This method significantly reduces the workload of data measure-ment in practical engineering applications.Our experimental results demonstrate that MSU predictions are highly similar to the real turbulent data in both spatio-temporal and individual aspects.Furthermore,the comparison results show that MSU predicts more precise results,even outperforming models that use all velocity field points.Compared with state-of-the-art methods,MSU has an average improvement of more than 45%in various indicators such as root mean square error(RMSE).Through comprehensive and authoritative physical verification,we estab-lished that MSU’s prediction results closely align with pressure field data obtained in real turbulence fields.This confirmation underscores the considerable potential of MSU for practical applications in real engineering scenarios.The code is available at https://github.com/zhangzm0128/MSU.

Robust autofocusing propagation in turbulence

Turbulence in complex environments such as the atmosphere and biological media has always been a great challenge to the application of beam propagation in optical communication, optical trapping and manipulation. To overcome this challenge, this study comprehensively investigates the robust propagation of traditional Gaussian and autofocusing beams in turbulent environments. In order to select stable beams that exhibit high intensity and high field gradient at the focal position in complex environments, Kolmogorov turbulence theory is used to simulate the propagation of beams in atmospheric turbulence based on the multi-phase screen method. We systematically analyze the intensity fluctuations, the variation of the coherence factor and the change in the scintillation index with propagation distance. The analysis reveals that the intensity fluctuations of autofocusing beams are significantly smaller than those of Gaussian beams, and the coherence of autofocusing beams is better than that of Gaussian beams under turbulence. Moreover, autofocusing beams exhibit less oscillation than Gaussian beams, indicating that autofocusing beams propagate in complex environments with less distortion and intensity fluctuation. Overall, this work clearly demonstrates that autofocusing beams exhibit higher stability in propagation compared with Gaussian beams, showing great promise for applications such as optical trapping and manipulation in complex environments.

Proton acceleration in plasma turbulence driven by high-energy lepton jets

The interaction of high energy lepton jets composed of electrons and positrons with background electron–proton plasma is investigated numerically based upon particle-in-cell simulation,focusing on the acceleration processes of background protons due to the development of electromagnetic turbulence.Such interaction may be found in the universe when energetic lepton jets propagate in the interstellar media.When such a jet is injected into the background plasma,theWeibel instability is excited quickly,which leads to the development of plasma turbulence into the nonlinear stage.The turbulent electric and magnetic fields accelerate plasma particles via the Fermi II type acceleration,where the maximum energy of both electrons and protons can be accelerated to much higher than that of the incident jet particles.Because of background plasma acceleration,a collisionless electrostatic shock wave is formed,where some pre-accelerated protons are further accelerated when passing through the shock wave front.Dependence of proton acceleration on the beam-plasma density ratio and beam energy is investigated.For a given background plasma density,the maximum proton energy generally increases both with the density and kinetic energy of the injected jet.Moreover,for a homogeneous background plasma,the proton acceleration via both turbulent fields and collisionless shocks is found to be significant.In the case of an inhomogeneous plasma,the proton acceleration in the plasma turbulence is dominant.Our studies illustrate a scenario where protons from background plasma can be accelerated successively by the turbulent fields and collisionless shocks.

Scaling Laws Behind Penetrative Turbulence:History and Perspectives

An unstably stratified flow entering into a stably stratified flow is referred to as penetrative convection,which is crucial to many physical processes and has been thought of as a key factor for extreme weather conditions.Past theoretical,numerical,and experimental studies on penetrative convection are reviewed,along with field studies providing insights into turbulence modeling.The physical factors that initiate penetrative convection,including internal heat sources,nonlinear constitutive relationships,centrifugal forces and other complicated factors are summarized.Cutting-edge methods for understanding transport mechanisms and statistical properties of penetrative turbulence are also documented,e.g.,the variational approach and quasilinear approach,which derive scaling laws embedded in penetrative turbulence.Exploring these scaling laws in penetrative convection can improve our understanding of large-scale geophysical and astrophysical motions.To better the model of penetrative turbulence towards a practical situation,new directions,e.g.,penetrative convection in spheres,and radiation-forced convection,are proposed.

An improved TDE technique for derivation of 2D turbulence structures based on GPI data in toroidal plasma

This paper reports an improved time-delay estimation(TDE)technique for the derivation of turbulence structures based on gas-puff imaging data.The improved TDE technique,integrating an inverse timing search and hierarchical strategy,offers superior accuracy in calculating turbulent velocity field maps and analyzing blob dynamics,which has the power to obtain the radial profiles of equilibrium poloidal velocity,blob size and its radial velocity,even the fluctuation analysis,such as geodesic acoustic modes and quasi-coherent mode,etc.This improved technique could provide important 2D information for the study of edge turbulence and blob dynamics,advancing the understanding of edge turbulence physics in fusion plasmas.

Cold filament frontogenesis and frontolysis induced by thermal convection turbulence using large eddy simulation

The frontogenetic processes of a submesoscale cold filament driven by the thermal convection turbulence are studied by a non-hydrostatic large eddy simulation.The results show that the periodic changes in the direction of the cross-filament secondary circulations are induced by the inertial oscillation.The change in the direction of the secondary circulations induces the enhancement and reduction of the horizontal temperature gradient during the former and later inertial period,which indicates that the frontogenetical processes of the cold filament include both of frontogenesis and frontolysis.The structure of the cold filament may be broken and restored by frontogenesis and frontolysis,respectively.The magnitude of the down-filament currents has a periodic variation,while its direction is unchanged with time.The coupling effect of the turbulent mixing and the frontogenesis and frontolysis gradually weakens the temperature gradient of the cold filament with time,which reduces frontogenetical intensity and enlarges the width of cold filament.

Gyro-Landau-fluid simulations of impurity effects on ion temperature gradient driven turbulence transport

The effects of impurities on ion temperature gradient(ITG)driven turbulence transport in tokamak core plasmas are investigated numerically via global simulations of microturbulence with carbon impurities and adiabatic electrons.The simulations use an extended fluid code(ExFC)based on a four-field gyro-Landau-fluid(GLF)model.The multispecies form of the normalized GLF equations is presented,which guarantees the self-consistent evolution of both bulk ions and impurities.With parametric profiles of the cyclone base case,well-benchmarked ExFC is employed to perform simulations focusing on different impurity density profiles.For a fixed temperature profile,it is found that the turbulent heat diffusivity of bulk ions in a quasi-steady state is usually lower than that without impurities,which is contrary to the linear and quasilinear predictions.The evolutions of the temperature gradient and heat diffusivity exhibit a fast relaxation process,indicating that the destabilization of the outwardly peaked impurity profile is a transient state response.Furthermore,the impurity effects from different profiles can obviously influence the nonlinear critical temperature gradient,which is likely to be dominated by linear effects.These results suggest that the improvement in plasma confinement could be attributed to the impurities,most likely through adjusting both heat diffusivity and the critical temperature gradient.

Performance of physical-informed neural network (PINN) for the key parameter inference in Langmuir turbulence parameterization scheme

The Stokes production coefficient(E_(6))constitutes a critical parameter within the Mellor-Yamada type(MY-type)Langmuir turbulence(LT)parameterization schemes,significantly affecting the simulation of turbulent kinetic energy,turbulent length scale,and vertical diffusivity coefficient for turbulent kinetic energy in the upper ocean.However,the accurate determination of its value remains a pressing scientific challenge.This study adopted an innovative approach by leveraging deep learning technology to address this challenge of inferring the E_(6).Through the integration of the information of the turbulent length scale equation into a physical-informed neural network(PINN),we achieved an accurate and physically meaningful inference of E_(6).Multiple cases were examined to assess the feasibility of PINN in this task,revealing that under optimal settings,the average mean squared error of the E_(6) inference was only 0.01,attesting to the effectiveness of PINN.The optimal hyperparameter combination was identified using the Tanh activation function,along with a spatiotemporal sampling interval of 1 s and 0.1 m.This resulted in a substantial reduction in the average bias of the E_(6) inference,ranging from O(10^(1))to O(10^(2))times compared with other combinations.This study underscores the potential application of PINN in intricate marine environments,offering a novel and efficient method for optimizing MY-type LT parameterization schemes.

Development of a 2D spatial displacement estimation method for turbulence velocimetry of the gas puff imaging system on EAST

A gas puff imaging(GPI)diagnostic has been developed and operated on EAST since 2012,and the time-delay estimation(TDE)method is used to derive the propagation velocity of fluctuations from the two-dimensional GPI data.However,with the TDE method it is difficult to analyze the data with fast transient events,such as edge-localized mode(ELM).Consequently,a method called the spatial displacement estimation(SDE)algorithm is developed to estimate the turbulence velocity with high temporal resolution.Based on the SDE algorithm,we make some improvements,including an adaptive median filter and super-resolution technology.After the development of the algorithm,a straight-line movement and a curved-line movement are used to test the accuracy of the algorithm,and the calculated speed agrees well with preset speed.This SDE algorithm is applied to the EAST GPI data analysis,and the derived propagation velocity of turbulence is consistent with that from the TDE method,but with much higher temporal resolution.

A sub-grid scale model for Burgers turbulence based on the artificial neural network method

The present study proposes a sub-grid scale model for the one-dimensional Burgers turbulence based on the neuralnetwork and deep learning method.The filtered data of the direct numerical simulation is used to establish thetraining data set,the validation data set,and the test data set.The artificial neural network(ANN)methodand Back Propagation method are employed to train parameters in the ANN.The developed ANN is applied toconstruct the sub-grid scale model for the large eddy simulation of the Burgers turbulence in the one-dimensionalspace.The proposed model well predicts the time correlation and the space correlation of the Burgers turbulence.

Turbine Passage Secondary Flow Dynamics and Endwall Heat Transfer Under Different Inflow Turbulence

This study presents endwall hydrodynamics and heat transfer in a linear turbine cascade at Re 5×105 at low and high intensities of turbulence.Results are numerically predicted using the standard SST model and Reθ-γtransition model as well as using the high-resolution LES separately.The major secondary flow components,comprising the horseshoe,corner,and passage vortices are recognized and the impact on heat or mass transfer is investigated.The complicated behavior of turbine passage secondary flow generation and establishment are impacted by the perspective of boundary layer attributes and inflow turbulence.The passage vortex concerning the latest big leading-edge vane is generated by the enlargement of the circulation developed at the first instance adjacent to the pressure side becomes powerful and mixes with other vortex systems during its migration towards the suction side.The study conclusions reveal that substantial enhancements are attained on the endwall surface,for the entire spanwise blade extension on the pressure surface,and in the highly 3-D region close to the endwall on the suction surface.The forecasted suction surface thermal exchange depicts great conformity with the measurement values and precisely reproduces the enhanced thermal exchange owing to the development and lateral distribution of the secondary flows along the midspan of the blade passage downstream.The impacts of the different secondary flow structures on the endwall thermal exchange are described in depth.