Turbulent Image Restoration in Atmosphere with Cyclopean Processing via Binocular Fusion

The outstanding issue to overcoming atmospheric turbulence on distant imaging is a fundamental interest and technological challenge.We propose a novel scenario and technique to restore the optical image in turbulent environmental by referring to Cyclopean image with binocular vision.With human visual intelligence,image distortion resulting from the turbulence is shown to be substantially suppressed.Numerical simulation results taking into account of the atmospheric turbulence,optical image system,image sensors,display and binocular vision perception are presented to demonstrate the robustness of the image restoration,which is compared with a single channel planar optical imaging and sensing.Experiment involving binocular telescope,image recording and the stereo-image display is conducted and good agreement is obtained between the simulation with perceptive experience.A natural extension of the scenario is to enhance the capability of anti-vibration or anti-shaking for general optical imaging with Cyclopean image.

Comparison of ERA5 turbulent fluxes at the air-sea interface with measurements from a wave-following platform

Turbulent fluxes at the air-sea interface were estimated with data collected in 2011-2020 with a low-profile platform named OCARINA during eight experiments in five regions:2011,2015,and 2016 in the Iroise Sea;2012 in the tropical Atlantic;2014 in the Chilie-Peru upwelling;2017 and 2018 in the Mediterranean Sea,and 2018 and 2020 in Barbados.The observations were carried out with moderate winds(2-10 m s^(-1))and average wave heights of 1.5 m.In this study,the authors used the fluxes calculated by the bulk method using OCARINA-sampled data as the input.These data can validate the fluxes estimated from ERAS reanalysis data.The OCARINA and ERA5 data were taken concomitantly.To do this,the authors established an algorithm to extract the OCARINA data as closely as possible to the reanalysis data in time and position.The measurements of the OCARINA platform can conclude on the relevance of the widely used reanalysis data.

Numerical Simulation of Turbulent Diffusion Flames of a Biogas Enriched with Hydrogen

Any biogas produced by the anaerobic fermentation of organic materials has the advantage of being an environmentally friendly biofuel.Nevertheless,the relatively low calorific value of such gases makes their effective utilization in practical applications relatively difficult.The present study considers the addition of hydrogen as a potential solution to mitigate this issue.In particular,the properties of turbulent diffusion jet flames and the related pollutant emissions are investigated numerically for different operating pressures.The related numerical simulations are conducted by solving the RANS equations in the frame of the Reynolds Stress Model in combination with the flamelet approach.Radiation effects are also taken into account and the combustion kinetics are described via the GRI-Mech 3.0 reaction model.The considered hydrogen fuel enrichment spans the range from 0%to 50%in terms of volume.Pressure varies between 1 and 10 atm.The results show that both hydrogen addition and pressure increase lead to an improvement in terms of mixing quality and have a significant effect on flame temperature and height.They also reduce CO_(2) emissions but increase NOx production.Prompt NO is shown to be the predominant NO formation mechanism.

The Turbulent Schmidt Number for Transient Contaminant Dispersion in a Large Ventilated Room Using a Realizable k-εModel

Buildings with large open spaces in which chemicals are handled are often exposed to the risk of explosions.Computational fluid dynamics is a useful and convenient way to investigate contaminant dispersion in such large spaces.The turbulent Schmidt number(Sc_(t))concept has typically been used in this regard,and most studies have adopted a default value.We studied the concentration distribution for sulfur hexafluoride(SF_(6))assuming different emission rates and considering the effect of Sc_(t).Then we examined the same problem for a light gas by assuming hydrogen gas(H_(2))as the contaminant.When SF_(6) was considered as the contaminant gas,a variation in the emission rate completely changed the concentration distribution.When the emission rate was low,the gravitational effect did not take place.For both low and high emission rates,an increase in S_(ct) accelerated the transport rate of SF_(6).In contrast,for H_(2) as the contaminant gas,a larger S_(ct) could induce a decrease in the H_(2) transport rate.

Analytical solutions of turbulent boundary layer beneath forward-leaning waves

As a typical nonlinear wave,forward-leaning waves can be frequently encountered in the near-shore areas,which can impact coastal sediment transport significantly.Hence,it is of significance to describe the characteristics of the boundary layer beneath forward-leaning waves accurately,especially for the turbulent boundary layer.In this work,the linearized turbulent boundary layer model with a linear turbulent viscosity coefficient is applied,and the novel expression of the near-bed orbital velocity that has been worked out by the authors for forward-leaning waves of arbitrary forward-leaning degrees is further used to specify the free stream boundary condition of the bottom boundary layer.Then,a variable transformation is found so as to make the equation of the turbulent boundary layer model be solved analytically through a modified Bessel function.Consequently,an explicit analytical solution of the turbulent boundary layer beneath forward-leaning waves is derived by means of variable separation and variable transformation.The analytical solutions of the velocity profile and bottom shear stress of the turbulent boundary layer beneath forward-leaning waves are verified by comparing the present analytical results with typical experimental data available in the previous literature.

Stochastic Analysis and Modeling of Velocity Observations in Turbulent Flows

Highly turbulent water flows,often encountered near human constructions like bridge piers,spillways,and weirs,display intricate dynamics characterized by the formation of eddies and vortices.These formations,varying in sizes and lifespans,significantly influence the distribution of fluid velocities within the flow.Subsequently,the rapid velocity fluctuations in highly turbulent flows lead to elevated shear and normal stress levels.For this reason,to meticulously study these dynamics,more often than not,physical modeling is employed for studying the impact of turbulent flows on the stability and longevity of nearby structures.Despite the effectiveness of physical modeling,various monitoring challenges arise,including flow disruption,the necessity for concurrent gauging at multiple locations,and the duration of measurements.Addressing these challenges,image velocimetry emerges as an ideal method in fluid mechanics,particularly for studying turbulent flows.To account for measurement duration,a probabilistic approach utilizing a probability density function(PDF)is suggested to mitigate uncertainty in estimated average and maximum values.However,it becomes evident that deriving the PDF is not straightforward for all turbulence-induced stresses.In response,this study proposes a novel approach by combining image velocimetry with a stochastic model to provide a generic yet accurate description of flow dynamics in such applications.This integration enables an approach based on the probability of failure,facilitating a more comprehensive analysis of turbulent flows.Such an approach is essential for estimating both short-and long-term stresses on hydraulic constructions under assessment.

Observing the air-sea turbulent heat flux on the trajectory of tropical storm Danas

Tropical cyclones constitute a major risk for coastal communities.To assess their damage potential,accurate predictions of their intensification are needed,which requires a detailed understanding of the evolution of turbulent heat flux(THF).By combining multiple buoy observations along the south north storm track,we investigated the THF anomalies associated with tropical storm Danas(2019)in the East China Sea(ECS)during its complete life cycle from the intensification stage to the mature stage and finally to its dissipation on land.The storm passage is characterized by strong winds of 10-20 m/s and a sea level pressure below 1000 hPa,resulting in a substantial enhancement of THF.Latent heat(LH)fluxes are most strongly affected by wind speed,with a gradually increasing contribution of humidity along the trajectory.The relative contributions of wind speed and temperature anomalies to sensible heat(SH)depend on the stability of the boundary layer.Under stable conditions,SH variations are driven by wind speed,while under near-neutral conditions,SH variations are driven by temperature.A comparison of the observed THF and associated variables with outputs from the ERA 5 and MERRA 2 reanalysis products reveals that the reanalysis products can reproduce the basic evolution and composition of the observed THF.However,under extreme weather conditions,temperature and humidity variations are poorly captured by ERA 5 and MERRA 2,leading to large LH and SH errors.The differences in the observed and reproduced LH and SH during the passage of Danas amount to 26.1 and 6.6 W/m^(2) for ERA 5,respectively,and to 39.4 and 12.5 W/m^(2) for MERRA 2,respectively.These results demonstrate the need to improve the representation of tropical cyclones in reanalysis products to better predict their intensification process and reduce their damage.

Artificial neural network-based one-equation model for simulation of laminar-turbulent transitional flow

A mapping function between the Reynolds-averaged Navier-Stokes mean flow variables and transition intermittency factor is constructed by fully connected artificial neural network(ANN),which replaces the governing equation of the intermittency factor in transition-predictive Spalart-Allmaras(SA)-γmodel.By taking SA-γmodel as the benchmark,the present ANN model is trained at two airfoils with various angles of attack,Mach numbers and Reynolds numbers,and tested with unseen airfoils in different flow states.The a posteriori tests manifest that the mean pressure coefficient,skin friction coefficient,size of laminar separation bubble,mean streamwise velocity,Reynolds shear stress and lift/drag/moment coefficient from the present two-way coupling ANN model almost coincide with those from the benchmark SA-γmodel.Furthermore,the ANN model proves to exhibit a higher calculation efficiency and better convergence quality than traditional SA-γmodel.

Analysis of particle dispersion in a turbulent flow considering particle rotation

Non-spherical particles exist widely in natural and industrial fluid systems and the motions of nonspherical particles are significantly different from that of spherical particles.In this paper,a simplified model of non-spherical particles considering particle drag correction,lift,and rotation was established.Based on the Eulerian-Lagrangian simulation,the dispersion characteristics of spherical and nonspherical particles with different Stokes numbers in a high-speed turbulent jet were analyzed and compared considering the effect of particle rotation.The results show that,the differences in particle dispersion and radial velocity fluctuation between non-spherical particles and spherical particles in the jet are significant,especially when Stokes number is large.Moreover,the effects of different type of forces on the dispersion of non-spherical particles and spherical particles were compared in detail,which revealed that the change of the Magnus force caused by the increase in the angular velocity of non-spherical particles plays a dominant role in the differences of particle dispersion.

Observed characteristics of flow,water mass,and turbulent mixing in the Preparis Channel

Preparis Channel is the very important exchange path of energy and materials between the northern Bay of Bengal and Andaman Sea(AS).A set of hydrographic measurements,a microstructure profiler,and a deep mooring were used to determine the characteristics of water masses,turbulent mixing,and flows in the Preparis Channel.The unprecedented short-term mooring data reveal that a deep current in the deep narrow passage(below 400 m)of the Preparis Channel flows toward the Bay of Bengal(BoB)with a mean along-stream velocity of 25.26 cm/s at depth of 540 m;above the deep current,there are a relatively weak current flows toward the AS with a mean along-stream velocity of 15.46 cm/s between 500 m and 520 m,and another weak current flows toward the BoB between 430 m and 500 m.Thus,a sandwiched vertical structure of deep currents(below 400 m)is present in the Preparis Channel.The volume transport below 400 m is 0.06 Sv(1 Sv=106 m^(3)/s)from the AS to the BoB.In the upper layer(shallower than 300 m),the sea water of the AS is relatively warmer and fresher than that in the BoB,indicating a strong exchange through the channel.Microstructure profiler observations reveal that the turbulent diffusivity in the upper layer of the Preparis Channel reaches O(10−4 m^(2)/s),one order larger than that in the interior of the BoB and over the continental slope of the northern AS.We speculate that energetic high-mode internal tides in the Preparis Channel contribute to elevated turbulent mixing.In addition,a local“hotspot”of turbidity is identified at the deep mooring site,at depth of about 100 m,which corresponds to the location of elevated turbulent mixing in the Preparis Channel.

Artificial neural network-based subgrid-scale models for LES of compressible turbulent channel flow

Fully connected neural networks(FCNNs)have been developed for the closure of subgrid-scale(SGS)stress and SGS heat flux in large-eddy simulations of compressible turbulent channel flow.The FCNNbased SGS model trained using data with Mach number Ma=3.0 and Reynolds number Re=3000 was applied to situations with different Mach numbers and Reynolds numbers.The input variables of the neural network model were the filtered velocity gradients and temperature gradients at a single spatial grid point.The a priori test showed that the FCNN model had a correlation coefficient larger than 0.91 and a relative error smaller than 0.43,with much better reconstructions of SGS unclosed terms than the dynamic Smagorinsky model(DSM).In a posteriori test,the behavior of the FCNN model was marginally better than that of the DSM in predicting the mean velocity profiles,mean temperature profiles,turbulent intensities,total Reynolds stress,total Reynolds heat flux,and mean SGS flux of kinetic energy,and outperformed the Smagorinsky model.

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.

Heat and Mass Transfers in a Two-Phase Stratified Turbulent Fluid Flow in a Geothermal Pipe with Chemical Reaction

This research focused on the study of heat and mass transfers in a two-phase stratified turbulent fluid flow in a geothermal pipe with chemical reaction. The derived non-linear partial differential equations governing the flow were solved using the Finite Difference Method. The effects of various physical parameters on the concentration, skin friction, heat, and mass transfers have been determined. Analysis of the results obtained indicated that the coefficient of skin friction decreased with an increase in Reynolds number and solutal Grasholf number, the rate of heat transfer increased with an increase in Eckert number, Prandtl number, and angle of inclination, and the rate of mass transfer increased with increase in Reynolds number, Chemical reaction parameter and angle of inclination. The findings would be useful to engineers in designing and maintaining geothermal pipelines more effectively.

Evaluating Parameterizations for Turbulent Fluxes over the Landfast Sea-Ice Surface in Prydz Bay, Antarctica

It is crucial to appropriately determine turbulent fluxes in numerical models.Using data collected in East Antarctica from 8 April to 26 November 2016,this study evaluates parameterization schemes for turbulent fluxes over the landfast seaice surface in five numerical models.The Community Noah Land Surface Model with Multi-Parameterizations Options(Noah_mp)best replicates the turbulent momentum flux,while the Beijing Climate System Model(BCC_CSM)produces the optimum sensible and latent heat fluxes.In particular,two critical issues of parameterization schemes,stability functions and roughness lengths,are investigated.Sensitivity tests indicate that roughness lengths play a decisive role in model performance.Based on the observed turbulent fluxes,roughness lengths over the landfast sea-ice surface are calculated.The results,which can provide a basis for setting up model parameters,reveal that the dynamic roughness length(z0m)increases with the increase of frictional velocity(u*)when u*≤0.4 m s^(−1) and fluctuates around 10^(−3 )m when u*>0.4 m s^(−1);thermal roughness length(z0t)is linearly related to the temperature gradient between air and sea-ice surface(ΔT)with a relation of lg(z0t)=−0.29ΔT−3.86;and the mean water vapor roughness length(z0q)in the specific humidity gradient(Δq)range ofΔq≤−0.6 g kg^(−1) is 10^(−6) m,3.5 times smaller than that in the range ofΔq˃−0.6 g kg^(−1).

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.

Different Turbulent Regimes and Vertical Turbulence Structures of the Urban Nocturnal Stable Boundary Layer

Turbulence in the nocturnal boundary layer(NBL)is still not well characterized,especially over complex underlying surfaces.Herein,gradient tower data and eddy covariance data collected by the Beijing 325-m tower were used to better understand the differentiating characteristics of turbulence regimes and vertical turbulence structure of urban the NBL.As for heights above the urban canopy layer(UCL),the relationship between turbulence velocity scale(VTKE)and wind speed(V)was consistent with the“HOckey-Stick”(HOST)theory proposed for a relatively flat area.Four regimes have been identified according to urban nocturnal stable boundary layer.Regime 1 occurs where local shear plays a leading role for weak turbulence under the constraint that the wind speed V<VT(threshold wind speed).Regime 2 is determined by the existence of strong turbulence that occurs when V>VT and is mainly driven by bulk shear.Regime 3 is identified by the existence of moderate turbulence when upside-down turbulence sporadic bursts occur in the presence of otherwise weak turbulence.Regime 4 is identified as buoyancy turbulence,when V>VT,and the turbulence regime is affected by a combination of local wind shear,bulk shear and buoyancy turbulence.The turbulence activities demonstrated a weak thermal stratification dependency in regime 1,for which within the UCL,the turbulence intensity was strongly affected by local wind shear when V<VT.This study further showed typical examples of different stable boundary layers and the variations between turbulence regimes by analyzing the evolution of wind vectors.Partly because of the influence of large-scale motions,the power spectral density of vertical velocity for upsidedown structure showed an increase at low frequencies.The upside-down structures were also characterized by the highest frequency of the stable stratifications in the higher layer.

Evolution of edge turbulent transport induced by L-mode detachment in the HL-2A tokamak

This paper presents the characteristics of L-mode detachment,together with the behavior of edge turbulent transport and plasma confinement on the HL-2A tokamak.Partially detached and pronounced detached states have been achieved in L-mode plasma.Stored energy was maintained before and after detachment.Edge turbulence and its transport have increased obviously in the partially detached state.In the pronounced detached state,redistribution of the density and temperature profiles due to detachment leads to low amplitude of electron temperature and pressure,as well as very weak edge turbulence and transport.Despite strong plasma radiation in the pronounced detached state,reduced edge turbulent transport contributes to maintaining stored energy in detached L-mode plasma in HL-2A.Different detachment states play an important role in the redistribution of density and temperature profiles,which requires further study.

A study on coherent structures and drag-reduction in the wall turbulence with polymer additives by TRPIV

An experimental measurement was performed us- ing time-resolved particle image velocimetry （TRPIV） to in- vestigate the spatial topological character of coherent struc- tures in wall-bounded turbulence of polymer additive solu- tion. The fully developed near-wall turbulent flow fields with and without polymer additives at the same Reynolds number were measured by TRPIV in a water channel. The compar- isons of turbulent statistics confirm that due to viscoelastic structure of long-chain polymers, the wall-normal velocity fluctuation and Reynolds shear stress in the near-wall region are suppressed significantly. Furthermore, it is noted that such a behavior of polymers is closely related to the decease of the motion of the second and forth quadrants, i.e., the ejection and sweep events, in the near-wall region. The spa- tial topological mode of coherent structures during bursts has been extracted by the new mu-level criteria based on locally averaged velocity structure function. Although the general shapes of coherent structures are unchanged by polymer additives, the fluctuating velocity, velocity gradient, velocity strain rate and vorticity of coherent structures during burst events are suppressed in the polymer additive solution com- pared with that in water. The results show that due to the polymer additives the occurrence and intensity of coherent structures are suppressed, leading to drag reduction.

Turbulent Kinetic Energy of Flow during Inhale and Exhale to Characterize the Severity of Obstructive Sleep Apnea Patient

This paper aims to investigate and present the numerical investigation of airflow characteristics using Turbulent Kinetic Energy(TKE)to characterize the upper airway with obstructive sleep apnea(OSA)under inhale and exhale breathing conditions.The importance of TKE under both breathing conditions is that it showan accuratemethod in expressing the severity of flow in sleep disorder.Computational fluid dynamics simulate the upper airway’s airflow via steady-state Reynolds-averaged Navier-Stokes(RANS)with k–ωshear stress transport(SST)turbulencemodel.The three-dimensional(3D)airway model is created based on the CT scan images of an actual patient,meshed with 1.29 million elements using Materialise Interactive Medical Image Control System(MIMICS)and ANSYS software,respectively.High TKE were noticed around the region after the necking(smaller cross-sectional area)during the inhale and exhale breathing.The turbulent kinetic energy could be used as a valuablemeasure to identify the severity of OSA.This study is expected to provide a better understanding and clear visualization of the airflow characteristics during the inhale and exhale breathing in the upper airway of patients for medical practitioners in the OSA research field.