Heat Transfer Enhancement of the Absorber Tube in a Parabolic Trough Solar Collector through the Insertion of Novel Cylindrical Turbulators

This study includes an experimental and numerical analysis of the performances of a parabolic trough collector(PTC)with and without cylindrical turbulators.The PTC is designed with dimensions of 2.00 m in length and 1.00 m in width.The related reflector is made of lined sheets of aluminum,and the tubes are made of stainless steel used for the absorption of heat.They have an outer diameter of 0.051 m and a wall thickness of 0.002 m.Water,used as a heat transfer fluid(HTF),flows through the absorber tube at a mass flow rate of 0.7 kg/s.The dimensions of cylindrical turbulators are 0.04 m in length and 0.047 m in diameter.Simulations are performed using the ANSYS Fluent 2020 R2 software.The PTC performance is evaluated by comparing the experimental and numerical outcomes,namely,the outlet temperature,useful heat,and thermal efficiency for a modified tube(MT)(tube with novel cylindrical turbulators)and a plain tube(PT)(tube without novel cylindrical turbulators).According to the results,the experimental outlet temperatures recorded 63.2°C and 50.5°C for the MT and PT,respectively.The heat gain reaches 1137.5 Win the MT and 685.8 Win the PT.Compared to the PT collector,the PTC exhibited a(1.64 times)higher efficiency.

Effect of the Arrangement of a New-Type of Turbulator Inserts on Heat Pipe Exchanger Performances

This research tests the effect of introducing turbulators of a new type into a circular tube heat exchanger under a constant and uniform longitudinal heatflux condition.A 45 mm diameter copper tube with a length of 1,350 mm is utilized with a solid disk being inserted inside the tube,which consists of three sections,each one containing two slots.The slot is cut at a 45 degree angle toward the inner tube surface,which results in diverging theflow toward the inner hot tube surface in order to enhance the heat transfer process.Air is considered as the workingfluid with Prandtl number 0.71.The Reynolds number spans the interval from 6,000–13,500,which indicates that the consideredflow is turbulent.The heat exchanger performance is studied and analyzed in terms of average Nusselt number.The experimental results show that the Nusselt number value is directly proportional to the increase of the Reynolds number,and the number of turbulators inserts.With the use of three novel turbulators,the heat transfer was about 3.15 times higher than that in the smooth tube and the friction factor was about 1.11.

Effects of turbulator shape,inclined magnetic field,and mixed convection nanofluid flow on thermal performance of micro-scale inclined forward-facing step

This investigation numerically examined the combined impacts of different turbulator shapes,Al_(2)O_(3)/water nanofluid,and inclined magnetic field on the thermal behavior of micro-scale inclined forward-facing step(MSIFFS).The length and height for all turbulators were considered 0.0979 and 0.5 mm,respectively,and the Reynolds number varied from 5000 to 10000.In order to compare the skin friction coefficient(SFC) and the heat transfer rate(HTR)simultaneously,the thermal performance factor parameter(TPF) was selected.The results show that all considered cases equipped with turbulators were thermodynamically more advantageous over the simple MSIFFS.Besides,using Al_(2)O_(3)/water nanofluid with different nanoparticles volume fractions(NVF) in the presence of inclined magnetic field(IMF)increased HTR.With an increment of NVF from 1% to 4% and magnetic field density(MFD) from 0.002 to 0.008 T,HTR and subsequently TPF improved.The best result was observed for MSIFFS equipped with a trapezoidal-shaped turbulator with 4% Al_(2)O_(3) in the presence of IMF(B=0.008 T).The TPF increased with the augmentation of Re,and the maximum value of it was 5.2366 for MSIFFS equipped with a trapezoidal-shaped turbulator with 4% Al_(2)O_(3),B=0.008 T,and Re=10000.

An advanced turbulator with blades and semi-conical section for heat transfer improvement in a helical double tube heat exchanger

In present work,a helical double tube heat exchanger is proposed in which an advanced turbulator with blades,semi-conical part,and two holes is inserted in inner section.Two geometrical parameters,including angle of turbulator’s blades(θ) and number of turbulator’s blades(N),are considered.Results indicated that firstly,the best thermal stratification is achieved at θ=180°.Furthermore,at the lowest studied mass flow rate(m = 8 × 10^(-3) kg/s),heat transfer coefficient of turbulator with blade angle of 180° is 130.77%,25%,and 36.36% higher than cases including without turbulator,with turbulator with blade angle of θ =240°,and θ =360°,respectively.Moreover,case with N=12 showed the highest overall performance.At the highest studied mass flow rate(m = 5.842 × 10^(-2) kg/s),heat transfer coefficient for case with N=12 is up to 54.76%,27.45%,and 6.56% higher than cases including without turbulator,with turbulator with N=6,and with turbulator with N=9,respectively.

Theory of Heat Exchange in Pipes With Turbulators With d/D=0.95÷0.90 And t/D=0.25÷1.00,and Also in Rough Pipes,by Air With Great Reynold’s Numbers Re=106

Mathematical modeling of heat exchange in air in pipes with turbulators with d/D=0.95÷0.90 and t/D=0.25÷1.00,as well as in rough pipes,with large Reynolds numbers(Re=106).The solution of the heat exchange problem for semicircular cross-section flow turbulizers based on multi-block computing technologies based on the factorized Reynolds equations(closed using the Menter shear stress transfer model)and the energy equation(on multi-scale intersecting structured grids)was considered.This method was previously successfully applied and verified by experiment in[1-4]for lower Reynolds numbers.The article continues the computational studies initiated in[1-4,25-27].

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.

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.

Role of Stokes Drift in Ocean Dynamics Under Typhoon Conditions in the Bohai Sea

The effect of Stokes drift production(SDP),which includes Coriolis-Stokes forcing,Langmuir circulation,and Craik-Lei-bovich vortexes,on the upper ocean during typhoon passage in the Bohai Sea(BS),China,is investigated by using a coupled wave-current model.The role of SDP in turbulent mixing and the further dynamics during the entire typhoon period are comprehensively stud-ied.Experimental results show that SDP greatly increases turbulent mixing at all depths under typhoon conditions by up to seven times that under normal weather conditions.SDP generally strengthens sea surface cooling by more than 0.4℃,with the maximum reduction in sea surface temperature(SST)at the during-typhoon stage exceeding 2℃,which is approximately seven times larger than that under normal weather conditions.The SDP-induced decrease in current speed can exceed 0.2ms^(-1),and the change in current direction is generally opposite the wind direction.These results suggest that Stokes drift depresses the effect of strong winds on currents by intensifying turbulent mixing.Mixed layer depth(MLD)is distinctly increased by O(1)during typhoons due to SDP and can deepen by more than 5m.In addition,the continuous effects of SDP on SST,current,and MLD at the after-typhoon stage indi-cate a hysteretic response between SDP and typhoon actions.

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.

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.

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.

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.

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.

Diffraction deep neural network-based classification for vector vortex beams

The vector vortex beam(VVB)has attracted significant attention due to its intrinsic diversity of information and has found great applications in both classical and quantum communications.However,a VVB is unavoidably affected by atmospheric turbulence(AT)when it propagates through the free-space optical communication environment,which results in detection errors at the receiver.In this paper,we propose a VVB classification scheme to detect VVBs with continuously changing polarization states under AT,where a diffractive deep neural network(DDNN)is designed and trained to classify the intensity distribution of the input distorted VVBs,and the horizontal direction of polarization of the input distorted beam is adopted as the feature for the classification through the DDNN.The numerical simulations and experimental results demonstrate that the proposed scheme has high accuracy in classification tasks.The energy distribution percentage remains above 95%from weak to medium AT,and the classification accuracy can remain above 95%for various strengths of turbulence.It has a faster convergence and better accuracy than that based on a convolutional neural network.

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.

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.

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.

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.

Experimental investigation of closed-loop active control to modulate coherent structures by mu-level method

The experimental research on zero-net-mass-flux jet closed-loop active control was conducted in the wind tunnel.The mu-level method successfully detected burst events of the coherent structures. The streamwise velocity signals in the turbulent boundary layer were measured by HWA. The drag reduction rate of 16.7% is obtained comparable to that of the open-loop control and saves 75% of the input energy at the asynchronous 100 V/160 Hz control case, which reflects the advantages of the closed-loop control. The experimental findings indicate that the intensity increases in the near-wall region.The perturbation of the PZT vibrators on the skewness factor is concentrated in the region y+< 60. The generation of highspeed fluids is depressed and the downward effect of high-speed fluids weakens. The alteration of energy distribution and the discernible impact of modulation between structures of varying scales are observed. The correlation coefficient exhibits a strong positive correlation, which indicates that the large-scale structures produce modulation effect on small-scale ones.The occurrence of burst events is effectively suppressed. The disturbance has the characteristics of stable periodicity,positive and negative symmetry, low intermittency, and high pulsation strength. The conditional phase waveform shows that the fluctuation amplitude increases, indicating amplitude modulation effects on coherent structures.

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.