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.

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.

J-TEXT achievements in turbulence and transport in support of future device/reactor

Following the reconstruction of the TEXT tokamak at Huazhong University of Science and Technology in China, renamed as J-TEXT, a plethora of experimental and theoretical investigations has been conducted to elucidate the intricacies of turbulent transport within the tokamak configuration. These endeavors encompass not only the J-TEXT device's experimental advancements but also delve into critical issues pertinent to the optimization of future fusion devices and reactors. The research includes topics on the suppression of turbulence, flow drive and damping, density limit, non-local transport, intrinsic toroidal flow, turbulence and flow with magnetic islands, turbulent transport in the stochastic layer, and turbulence and zonal flow with energetic particles or helium ash. Several important achievements have been made in the last few years, which will be further elaborated upon in this comprehensive review.

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.

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.

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.

Wave Attenuation and Turbulence Driven by Submerged Vegetation Under Current-Wave Flow

A set of laboratory experiments are carried out to investigate the effect of following/opposing currents on wave attenuation.Rigid vegetation canopies with aligned and staggered configurations were tested under the condition of various regular wave heights and current velocities,with the constant water depth being 0.60 m to create the desired submerged scenarios.Results show that the vegetation-induced wave dissipation is enhanced with the increasing incident wave height.A larger velocity magnititude leads to a greater wave height attenuation for both following and opposing current conditions.Moreover,there is a strong positive linear correlation between the damping coefficientβand the relative wave height H_(0)/h,especially for pure wave conditions.For the velocity profile,the distributions of U_(min)and U_(max)show different patterns under combined wave and current.The time-averaged turbulent kinetic energy(TKE)vary little under pure wave and U_(c)=±0.05 m/s conditions.With the increase of flow velocity amplitude,the time-averaged TKE shows a particularly pronounced increase trend at the top of the canopy.The vegetation drag coefficients are obtained by a calibration approach.The empirical relations of drag coefficient with Reynolds and Keulegane-Carpenter numbers are proposed to further understand the wave-current-vegetation interaction mechanism.

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.

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.

Influence of the upper mixed layer depth on Langmuir turbulence characteristics

The upper mixed layer depth(h)has a significant seasonal variation in the real ocean and the low-order statistics of Langmuir turbulence are dramatically influenced by the upper mixed layer depth.To explore the influence of the upper mixed layer depth on Langmuir turbulence under the condition of the wind and wave equilibrium,the changes of Langmuir turbulence characteristics with the idealized variation of the upper mixed layer depth from very shallow(h=5 m)to deep enough(h=40 m)are studied using a non-hydrostatic large eddy simulation model.The simulation results show that there is a direct entrainment depth induced by Langmuir turbulence(h_(LT))within the thermocline.The normalized depthaveraged vertical velocity variance is smaller and larger than the downwind velocity variance for the ratio of the upper mixed layer to a direct entrainment depth induced by Langmuir turbulence h/h_(LT)<1 and h/h_(LT)>1,respectively,indicating that turbulence characteristics have the essential change(i.e.,depth-averaged vertical velocity variance(DAVV)DADV for Langmuir turbulence)between h/h_(LT)<1 and h/h_(LT)>1.The rate of change of the normalized depth-averaged low-order statistics for h/h_(LT)<1 is much larger than that for h/h_(LT)>1.The reason is that the downward pressure perturbation induced by Langmuir cells is strongly inhibited by the upward reactive force of the strong stratified thermocline for h/h_(LT)<1 and the eff ect of upward reactive force on the downward pressure perturbation becomes weak for h/h_(LT)>1.Hence,the upper mixed layer depth has significant influences on Langmuir turbulence characteristics.

Aero-Hydrodynamic Coupled Dynamic Characteristics of Semi-Submersible Floating Offshore Wind Turbines Under Inflow Turbulence

In this study,the frequency characteristics of the turbulent wind and the effects of wind-wave coupling on the low-and high-frequency responses of semi-submersible floating offshore wind turbines(FOWT)are investigated.Various wave load components,such as first-order wave loads,combined first-and second-order difference-frequency wave loads,combined first-and second-order sum-frequency wave loads,and first-and complete second-order wave loads are taken into consideration,while different turbulent environments are considered in aerodynamic loads.The com-parison is based on time histories and frequency spectra of platform motions and structural load responses and statistical values.The findings indicate that the second-order difference-frequency wave loads will significantly increase the natural frequency of low-frequency motion in the responses of the platform motion and structure load of the semi-submersible platform,which will cause structural fatigue damage.Under the action of turbulent wind,the influences of second-order wave loads on the platform motion and structural load response cannot be ignored,especially under extreme sea conditions.Therefore,in order to evaluate the dynamic responses of semi-submersible FOWT more accurately,the actual environment should be simulated more realistically.

Theoretical analysis of the optical rotational Doppler effect under atmospheric turbulence by mode decomposition

The optical rotational Doppler effect associated with orbital angular momentum provides a new means for rotational velocity detection.In this paper,we investigate the influence of atmospheric turbulence on the rotational Doppler effect.First,we deduce the generalized formula of the rotational Doppler shift in atmospheric turbulence by mode decomposition.It is found that the rotational Doppler signal frequency spectrum will be broadened,and the bandwidth is related to the turbulence intensity.In addition,as the propagation distance increases,the bandwidth also increases.And when C_(n)^(2)≤5×10^(-15)m^(-2/3)and 2z≤2 km,the rotational Doppler signal frequency spectrum width d and the spiral spectrum width d_(0)satisfy the relationship d=2d_(0-1).Finally,we analyze the influence of mode crosstalk on the rotational Doppler effect,and the results show that it destroys the symmetrical distribution of the rotational Doppler spectrum about 2l·Ω/2π.This theoretical model enables us to better understand the generation of the rotational Doppler frequency and may help us better analyze the influence of the complex atmospheric environment on the rotational Doppler frequency.

Diffraction deep neural network based orbital angular momentum mode recognition scheme in oceanic turbulence

Orbital angular momentum(OAM)has the characteristics of mutual orthogonality between modes,and has been applied to underwater wireless optical communication(UWOC)systems to increase the channel capacity.In this work,we propose a diffractive deep neural network(DDNN)based OAM mode recognition scheme,where the DDNN is trained to capture the features of the intensity distribution of the OAM modes and output the corresponding azimuthal indices and radial indices.The results show that the proposed scheme can recognize the azimuthal indices and radial indices of the OAM modes accurately and quickly.In addition,the proposed scheme can resist weak oceanic turbulence(OT),and exhibit excellent ability to recognize OAM modes in a strong OT environment.The DDNN-based OAM mode recognition scheme has potential applications in UWOC systems.

Vibration and Sound Radiation of Cylindrical Shell Covered with a Skin Made of Micro Floating Raft Arrays Excited by Turbulence

To reduce the vibration and sound radiation of underwater cylindrical shells,a skin composed of micro floating raft arrays and a compliant wall is proposed in this paper.A vibroacoustic coupling model of a finite cylindrical shell covered with this skin for the case of turbulence excitation is established based on the shell theories of Donnell.The model is solved with the modal superposition method to investigate the effects of the structural parameters of micro floating raft elements on the performance of reducing vibration and sound radiation of the cylindrical shell of this skin.The results indicate that increasing the stiffness ratio,damping ratio,mass ratio,or decreasing the interval betweenmicro floating raft elements can improve the vibration and sound radiation reduction performance of this skin over the frequency range 0∼2000 Hz.Moreover,the mean quadratic velocity level and sound radiation power level of the finite cylindrical shell with this skin can be reduced by 12.00 dB and 9.65 dB respectively compared to the finite cylindrical shell with homogeneous viscoelastic coating in the frequency range from0∼2000Hz,implying a favorable performance of this skin for reducing the vibration and sound radiation of cylindrical shells.

Numerical simulation of gas–liquid flow in the bubble column using Wray–Agarwal turbulence model coupled with population balance model

In this paper,an improved computational fluid dynamic(CFD)model for gas-liquid flow in bubble column was developed using the one-equation Wary-Agarwal(WA)turbulence model coupled with the population balance model(PBM).Through 18 orthogonal test cases,the optimal combination of interfacial force models,including drag force,lift force,turbulent dispersion force.The modified wall lubrication force model was proposed to improve the predictive ability for hydrodynamic behavior near the wall of the bubble column.The values simulated by optimized CFD model were in agreement with experimental data,and the errors were within±20%.In addition,the axial velocity,turbulent kinetic energy,bubble size distribution,and the dynamic characteristic of bubble plume were analyzed at different superficial gas velocities.This research work could provide a theoretical basis for the extension of the CFD-PBM coupled model to other multiphase reactors..