Xifan Duan,Zhiguo Yuan,Youzhi Liu,Hangtian Li,Weizhou Jiao

Shanxi Province Key Laboratory of Higee-Oriented Chemical Engineering,North University of China,Taiyuan 030051,China

Keywords: Chemical process strengthening equipment Rotating packed bed Computational fluid dynamics Particle image velocimetry Sieve packing

ABSTRACT Rotating packed bed has high efficiency of gas–liquid mass transfer.So it is significant to investigate fluid motion in rotating packed bed.Numerical simulations of the effects of packing feature size on liquid flow characteristics in a rotating packed bed are reported in this paper.The particle image velocimetry is compared with the numerical simulations to validate the turbulent model.Results show that the liquid exists in the packing zone in the form of droplet and liquid line,and the cavity is droplet.When the radial thickness of the packing is less than 0.101 m,liquid line and droplets appear in the cavity.When rotational speed and radial thickness of the packing increase,the average diameter of the droplets becomes smaller,and the droplet size distribution becomes uniform.As the initial velocity of the liquid increases,the average droplet diameter increases and the uniformity of particle size distribution become worse.The droplet velocity increases with the radial thickness of the packing increasing,and gradually decreases when it reaches the cavity region.The effect of packing thickness is most substantial through linear fitting.The predicted and simulated values are within ±15%.The cumulative volume distribution curves of the experimental and simulated droplets are consistent with the R-R distribution.

1.Introduction

As a reformative process intensification equipment,the high gravity rotating packed bed (RPB) has a unique structure and performance,which results in broad industrial application prospects and development potential.The device has the advantages of small volume,high mass transfer coefficient,and wide application range,which can greatly reduce the scale of traditional factories and improve space utilization [1].In recent years,researchers have used RPB for numerous industrial applications in desulfurization,destocking,industrial wastewater treatment,industrial dust removal,industrial deamination,liquid membrane separation,and nanomaterial preparation.

At present,scholars mainly use the two techniques of numerical simulation and flow field visualization to explore the hydrodynamic characteristics in an RPB.Characteristics of the flow field in the reactor are visually explored by using technology such as the Pisto method [2],the hot wire anemometer method [3],the laser Doppler velocity measurement technology [4],and the particle image velocimetry (PIV) technology [5].Burns and Ramshaw[6]used a camera to study the flow of liquid in an RPB at different speeds and volumes.Guo[7]studied liquid flow pattern in an RPB under different packing types by using a TV camera rotating synchronously with the rotor and observed a liquid line flow on the surface and space of the packing.Zhang [8]used high-speed stroboscopic equipment to observe different areas of an RPB under two kinds of packing,namely,foam metal and RS corrugated mesh.Yanget al.[9]used PIV technology to investigate the effect of packing thickness and operating parameters on droplet diameter and velocity in the RPB cavity.Sunet al.[10]used a high-speed camera to capture the flow pattern of liquid in an RPB under different wire diameter specifications.Sanget al.[11]used high-speed camera technology to observe liquid flow in the RPB cavity under different operating parameters.Gaoet al.[12]used a high-speed camera to capture the velocity,diameter,and distribution of liquid in a highspeed disperser under different radial distances and operating parameters.Cerqueiraet al.[13]verified the validity of the PIV program.These research methods provided various possibilities for subsequent research and promoted the visualization of the liquid flow field.This paper borrows on these research methods.

Xieet al.[14]established a 2D physical model of an RPB and used computational fluid dynamics (CFD) technology to simulate the flow pattern of the liquid using a fluid volume fractional multiphase flow model (VOF) as a two-phase flow model.Guoet al.[15]established a 3D physical model of an RPB.The VOF model,the sliding mesh model(Sliding Meshes,SM),and the realizablek-ε model were used to simulate the two gas–liquid phases in an RPB.Yanget al.[16]established a 3D physical model for an RPB and simulated the single-phase flow field.Edgaret al.[17]simulated the velocity distribution of two gas–liquid phases in an RPB using a multiphase flow model with a water-absorbing SO2system.Shiet al.[18]investigated the velocity distribution of liquid in an RPB by numerical simulation.Shiet al.[19]established a 2D physical model of an RPB and numerically simulated the liquid flow.Liet al.[20]also studied the flow of liquid in a counter-rotating packed bed using CFD and PIV techniques.Xuet al.[21]established a 2D physical model for the corrugated packing rotating bed,and the gas flow in the packing affects droplet breakage and polymerization.Ouyanget al.[22]used a 2D model to discuss the liquid flow characteristics of viscous fluids in different regions of an RPB.Luet al.[23–24]used a porous media model for CFD simulations of gas–liquid two-phase flow in RPBs.Xieet al.[25]proposed a new mesoscale 3D CFD model to predict the liquid flow in an RPB.Mortensenet al.[26]accurately captured power maps,flow numbers,and detailed velocity fields in mixed and dispersed regions using the CFD model.The 2D model is better than the 3D model in the study of radial thickness of the filler.

Scholars’ research on fluid mechanics in RPB focuses on liquid flow morphology and droplet velocity.However,packing characteristics and packing type are not clear about the liquid flow with operating parameters.The liquid flow inside an RPB is complicated,and the mass transfer efficiency between different regions is very different.If flow characteristics of the liquid and its formation reasons can be explored,the gas–liquid mass transfer efficiency can be enhanced,and the improvement and reaction of the packing can be achieved.The design of the device provides guidance.Therefore,the counter-rotating packed bed was taken as the research object,and the liquid in the rotating bed of the sieve packing with different characteristic sizes was visualized by PIV technology.The rationally simplified physical model was numerically simulated.The flow characteristics of the liquid under different characteristic sizes of packing were obtained through experimental observation and simulation results,which provided a theoretical basis for further optimization of the RPB.

2.Experimental

2.1.Experimental apparatus and measurement principle

The 2D PIV system was purchased from the PIV system developed by the Shanxi Province Super Gravity Chemical Engineering Technology Research Center for the US TSI Company and mainly composed of the following systems,as shown in Table 1.

Table 1PIV system composition and performance

The PIV system uses a CCD camera to capture the fluid in the flow field and obtains a moving image of the tracer particles by analysis.CCD cameras have better imaging quality than highspeed cameras,and the post-imaging processing is faster,suitable for continuous photography.The basic principle is that the tracer particles in pulse time interval Δtcan be processed by an image processing software to obtain displacementSof the particles,thereby deriving the average velocity of the tracer particles.When Δtapproaches 0,the instantaneous velocity of the particles can be obtained,as shown in Fig.1(a).The velocity distribution information of the flow field in the entire reactor can be determined by photographing all particles in the flow field.

The cross-correlation algorithm was used for image processing,and the two exposure images taken by a CCD camera were independently compared.Three-time Fourier transform calculation was needed in the calculation of the cross-correlation algorithm.If all particles in the query area are evenly displaced,the second image taken after Δttime can be considered the displacement of the first image,as shown in Fig.1(b).

2.2.Experimental device and process

The fluid in the counter-current RPB was photographed by PIV visualization technology.The influence of different packing feature sizes on the liquid and its initial velocity was studied.

The type of packing used in the counter-current RPB was sieve packing as shown in Fig.2(b) (feature size: 134,168,202,and 236 mm),the physical and specification parameters as shown in Table 2.

Table 2Packing Specifications

The experimental flow is shown in Fig.2(a).After the liquid is pressurized by the metering pump,it enters the liquid distributor in the counter-rotating RPB from the shut-off valve and the liquid flow meter,and is sprayed on the inner edge of the RPB.After the high-speed rotating packing is sheared,it converges on the inner wall surface of the casing,is finally discharged from the liquid outlet,and enters the liquid storage tank for recycling.After the gas is pressurized by the fan,it is adjusted by the shut-off valve and the gas flow meter,and then enters the RPB from the gas inlet,from the outer edge of the packing to the inner edge.The flow in the countercurrent contacts the liquid and is finally discharged from the middle gas outlet (experiment mainly studies liquid flow behavior when the value of the gas inflow RPB is adjusted to 0).During the operation of the counter-current RPB system,the laser in the pulsed laser is projected to the shooting area through the light guiding arm,the CCD camera shoots the fluid form in the flow field,and the synchronizer finally transmits the captured image to the computer.The characteristics of the liquid’s morphology,velocity field,and droplet size are obtained through posttreatment analysis.Fig.2(b) shows the PIV bench.

3.CFD Model

3.1.2D physical model

The flow pattern of liquid in the counter-rotating packed bed sieve plate packing was numerically simulated by establishing a 2D model for analysis and comparison with the PIV visualization experiment results.

Fig.1.(a) PIV image processing schematic.(b) Schematic diagram of cross-correlation algorithm.

Fig.2.(a) PIV experimental process flow chart.(b) PIV physical map.

Sieve packing was simplified to a 2D physical model with squares and circles,and the spacing of each circular aperture in the packing layer was reduced to squares that were evenly arranged circumferentially with a side length of 3 mm.Circular holes in the packing layer were reduced to spaces between the squares in the 2D model.As a liquid channel,the spacing was 4 mm,and circular holes in the liquid distributor were simplified to a straight line with a distance of 3 mm.The spacing between each square was the same as that of the real packing layers for a total of five layers and a spacing of 14 mm.

The packing had five layers,and feature sizes of each layer of packing from inside to outside were 100,134,168,202,and 236 mm,respectively.Physical models of Layers 2,3,and 4 were numerically simulated,as shown in Fig.3.

3.2.Meshing and irrelevance test

The accuracy and economics of calculations in numerical simulation are mainly determined by mesh quality,and mesh size determines the number and quality of the mesh.In ICEM CFD software,the unstructured mesh is used to mesh the quadrilateral.The packing area is set to the moving regions,and the remaining area is set to the stationary regions for mesh division.This paper only shows the fourth layer meshing diagram.Fig.4 shows that the meshing model of all layers is distinguished by the number of moving area (filling area) grids,as shown in Table 3.

Table 3Meshing parameter table

Fig.3.2D RPB physical model and schematic view of packing.

Fig.4.2D meshing and partial schematic.

Grid independence tests were performed on all models to determine the influence of grid size on calculation results.For grid sizes of 0.1,0.2,and 0.3 mm,the grid independence test was performed at a speed of 600 r·min-1and an initial liquid velocity of 1 m·s-1.Found a grid size of 0.1 mm,not only the number of grids generated,but also the calculation time is too long.For a grid size of 0.3 mm,the number of grids is small,but the error with the experimental data is large.A grid size of 0.2 mm can meet the needs of the calculation,and the error value compared with the experimental data is 6%.Therefore,all models were meshed with a mesh size of 0.2 mm.Meshing parameters are shown in Table 3.

3.3.Boundary conditions

Boundary conditions were set in ICEM CAD and Fluent software,and the gas–liquid two-phase flow was simulated.Fig.4 shows that the liquid inlet is set to velocity-inlet,the unit is m·s-1,and the liquid volume fraction is set to 1; the outermost edge is set to pressure-outlet,the unit is Pa,and the value is based on speed.The size is set.The inner edge is set to pressure-inlet for the inner wall surface except for the liquid inlet,the unit is Pa,and the value is 0.All walls are set to no-slip,and the contact angle is 45°.

3.4.Turbulence model

The flow field in the RPB is a complex,highly turbulent,strong swirling flow field,whereas the fluid flow in the RPB has a strong anisotropy.The Reynoldsstress model(RSM)isa typical time-processing turbulentmotion model.Comparedwiththek-ε two-equation model,RSM is more suitable for anisotropic rotational flow and can provide more accurate numerical simulation results[27].

The RSM model used in Fluent software is expressed below[28]:

wheregis the gas phase; μ is the viscosity,kg·m-1·s-1;Pijis the shear stress generation term; φijis the pressure strain term;kis the turbulent kinetic energy; and ε is the dissipation rate.In Eq.(1),turbulent kinetic energy and dissipation rate exist and must be supplemented when using the RSM equation,as follows:

whereGijis the buoyancy-generating term.When the fluid is incompressible,Gij=0; and μtis the kinematic viscosity,m2·s-1,which is calculated by the following formula:

In Fluent,C1ε is 1.44,C2ε is 1.92,andC3ε is 0.09.σkis 0.82,and σεis 1.0,Both are empirical constants,and default values are used.

3.5.VOF model

The liquid motion of gas–liquid two-phase flow in an RPB is numerically simulated.Assuming that the two phases are two fluids that are incompatible with each other,the VOF model is suitable for stratified flow or free surface flow,as expressed below:

where 0 < αq< 1 (gas < αq< liquid),and a value between 0 and 1 indicates that the calculation unit is multiphase mixed.The gas–liquid interface based on the VOF model is solved as follows:

wherelis the liquid phase,gis the gas phase,tis the time,and αqis the volume fraction of theqphase.The momentum conservation equation based on the VOF model is expressed as follows:

where ρ is the density,and μ is the viscosity,which is calculated from the value of the volume fraction of each component.They are expressed as follows:

In addition,the interface of each phase in each computing cell grid needs to be constructed by a certain method,as shown in Fig.5.

3.6.SM model

An SM model should be selected for the particularity of fluid motion in an RPB [28].Compared with other models,it considers the flow field to be unsteady,and the numerical simulation fully conforms to the very strong interaction between the rotating objects in the flow field,thus ensuring calculation accuracy.

The integral form of the scalar on the arbitrary control body of the interface moving mesh is as follows:

where ρ is the fluid density,u is the fluid velocity vector,ugis the moving mesh velocity,Γ is the diffusion coefficient,andSφis the source term.The flow field motion of the relative velocity exists in an RPB,and the calculation result has periodicity.Therefore,when using the SM model for flow field motion calculation and the monitored liquid content changes periodically or is in a steady state,the calculation can be considered to have reached a convergence state.

3.7.Solution method

In the unsteady environment,the SIMPLE algorithm was used to calculate the equation of pressure and velocity coupling in the flow field.The volume fraction equations of each phase were calculated by the spatial discretization Geo-Reconstruct.Second-order upwind type discrete momentum and turbulent kinetic energy equations were used.The number of time steps in each working condition was 1×104,and the time step was set to 10-6–10-5according to the speed (400,600,800,1000,and 1200 r·min-1)in each time step.A maximum number of iteration steps of 20 was performed to achieve computational convergence with a time residual of 10-5.In the initial calculation,the gas phase singlephase flow simulation was first carried out in a counter-rotating packed bed.When gas filled the entire RPB reactor,the VOF model was used for transient calculation.Air was set to the continuous phase,water was set to the dispersed phase.

4.Results and Discussion

4.1.Liquid form in RPB

The experimental and simulation results in Fig.6 show the flow pattern of the liquid under different packing feature sizes.The red area is liquid (the gas–liquid phase interface is set to 0.4),and the blue area is air.A comparison of PIV and CFD shows that the liquid in the cavity is mainly in the form of droplets,and the packing zone mainly exists as droplet flow and liquid line flow.When the characteristic size of the packing is gradually reduced,the shape of the droplet gradually changes from a circular shape to an elliptical shape,and many droplets of various shapes appear but mainly exist as elliptical droplets.The flow and liquid line flow in Fig.6(d) and (D) show that when packing size is particularly small,liquid dispersion is extremely uneven,thereby reducing the specific surface area of the liquid,which is not conducive to the mass transfer of gas and liquid.The packing has a great influence on the breaking of the liquid.Liquid become liquid droplet and liquid line.

Fig.5.Phase interface processing method (a: Actual mask,b: Geometric reconstruction,and c: Material acceptance).

4.2.Average droplet diameter

The liquid was sheared by RPB and dispersed into numerous droplets flying in the cavity area and the filling area.During this process,the liquid droplets were subjected to various forces,thereby causing self-rupture and polymerization,as shown by Eq.(11) [20]:

whereWeis the Weber number,ρgis the air density,νlis the liquid velocity,νgis the gas velocity,dis the droplet diameter,and σ is the liquid surface tension coefficient.Assuming that the liquid is moving within a steady stream of air (under ideal conditions),the gas velocity is 0,and the maximumWeis 8.05 under all experimental operating conditions.Therefore,the liquid in the entire RPB hardly breaks.Moreover,the phenomenon of aggregation is likely due to the difference in the droplet velocity of the packing structure.

4.3.Effect of rotation speed on the average diameter of droplets

Fig.7showsthat when therotationspeedincreases from 400 r·min-1to1200 r·min-1,theaveragedropletdiameter varies between 0.4 and 1.05 mm; when the rotation speed continuously increases,the average droplet diameter continuously decreases.This finding is explained as follows.On the one hand,as the rotational speed increases in the super-gravity field according to the Gibbs function,the work that the liquid can overcome the surface tension and the shear force of the liquid increase.The stability of the liquid in space is reduced,such that the liquid breaks into smaller droplets.On the other hand,the relative speed between the liquids is continuously increased due to the increase of the rotational speed,which improves the shearing action of the packing on the liquid,resulting in a continuous decrease in droplets.In addition,as the rotational speed increases,the tendency of the droplet to decrease gradually decreases,and the average diameter of the droplet gradually stabilizes.

4.4.Effect of the characteristic size of the packing on the average diameter of the liquid

Fig.8 shows the effect of the characteristic size of the packing on the average diameter of the droplets.The average diameter of the droplets under the characteristic dimensions of the different packing is compared with Fig.6.As the size of the packing increases,the average diameter of the droplets decreases.A possible reason is that on the one hand,when the characteristic size of the packing is increased,the shearing force of the packing to the liquid also increases.When the liquid is continuously sheared by the multilayer packing,the average diameter of the droplet is bound to decrease,increasing the specific surface area of the liquid,which is conducive to gas–liquid mass transfer.On the other hand,when rotational speed and initial velocity of the liquid are constant,the amount of liquid entering the packing is determined.When the characteristic size of the packing is continuously increased,the unit of the liquid in the packing is reduced,and the liquid undergoes more work,resulting in a smaller droplet diameter.However,this situation also reduces the frequency of renewal of the liquid line on the surface of the packing.At this time,when the liquid reaches the cavity region,the droplets gradually become rounded due to the influence of surface tension,as shown in Fig.6(d) and (D).When the characteristic size of the packing increases from 0.068 m to 0.084 m,the average diameter of the droplets sharply decreases.When the characteristic size of the packing changes,the predominant form of liquid in the RPB changes from big droplet to little droplet or liquid line to droplet.

4.5.Effect of initial liquid velocity on average droplet diameter

Fig.9 shows that as the initial velocity of the liquid increases,the average diameter of the droplets increases.At a certain rotation speed and packing thickness,the corresponding liquid amount increases when the initial velocity of the liquid increases.The liquid passes through the packing under the condition that the shear force of the packing is constant due to the large gap between the packing of the sieve plates.After the action,the number density of the droplets in the cavity region becomes larger,increasing the probability of coalescence between the droplets,thereby making the droplet diameter larger.Moreover,when the initial velocity of the liquid increases,its velocity becomes higher than that when entering the packing zone.Under the influence of the space structure of sieve packing,the entire packing zone passes faster,and the filling of the packing is not easy.Therefore,the appropriate amount of liquid should be selected according to the structure of the packing.

4.6.Fitting correlation of droplet average diameter

The average diameterdof the droplets of the simulated data was fitted to each parameter,and the following correlation was obtained:

Fig.6.Liquid shape diagram in RPB (N=600 r·min-1, u0=1 m·s-1).CFD: (a)R=0.118 m,(b) R=0.101 m,(c) R=0.084 m,and (d) R=0.067 m.PIV: (A)R=0.118 m,(B) R=0.101 m,(C) R=0.084 m,and (D) R=0.067 m.

The above formula shows that when rotational speedNand characteristic dimensionRof the packing increase,and initial liquid velocityu0decreases,the average diameter of the droplet decreases.Fig.10 is a correlation fit error graph showing that the relative error between the simulated value and the predicted value of the average diameter of the droplet is within ±15%,indicating that the fitting correlation is reliable.

Fig.7.Variation of average droplet diameter with speed.

Fig.8.Variation of average droplet diameter as a function of packing size.

Fig.9.Variation of the average diameter of droplets with initial velocity of the liquid.

4.7.Droplet diameter distribution

Fig.10.Fitting error plot of simulated and predicted values of droplet average diameter.

The size and distribution of the average droplet diameter are not only important for improving the gas–liquid mass transfer efficiency in RPB but also provide a theoretical basis for the application of RPB industrialization.Therefore,the droplet distribution in the cavity region was studied,and the probability density distribution and cumulative volume distribution curve of droplets under different packing feature sizes were obtained in this paper.The packing geometry size was optimized through analysis and comparison.

The diameter of the droplets under each simulated condition was divided into 25 groups,and the distribution of the characteristic size of the packing to the probability density distribution of the droplet diameter was obtained,as shown in Fig.11.

Fig.11 shows that the droplet density probability density distribution curve and the normal distribution have small errors,showing a serious tailing phenomenon.As the size of the packing features increases,the curve gradually becomes high and narrow,and the trend becomes steeper.The droplet size decreases,and the droplet size range becomes narrower.For the correlation of droplet size distribution,the most widely used Rosin-Rammler distribution function(Rosin-Rammler,R-R)[29]is generally used.The distribution of the function is easy to understand,and the parameters used have practical significance.Therefore,the R-R distribution function was used in this paper to fit the cumulative volume distribution of the liquid in the countercurrent rotating packed bed and is expressed as follows:

whereVis the cumulative volume fraction of the droplet diameter less thand,which is dimensionless;dis the droplet diameter mm;deis the corresponding droplet diameter when the cumulative volume fraction is 0.632,called the characteristic diameter mm;andmis the uniformity index,which is dimensionless,indicating the width distribution of the droplet diameter.The larger the value is,the better the uniformity of droplet dispersion.

Fig.12 compares the experimental and calculated values for the cumulative volume distribution model of droplets under the characteristic dimensions of each packing,where theX-axis is the droplet sized,and theY-axis is less than the cumulative volume fraction underd.The minimum fitting curveR2under all working conditions is greater than 0.99841,indicating that the R-R model can well describe the cumulative volume distribution of droplet size in the countercurrent rotating packed bed.When the characteristic size of the packing increases,the curve becomes steep,the droplet size moves toward the decreasing direction,and the uniformity of the droplet size distribution becomes better,which is beneficial for improving the RPB gas–liquid two-phase mass transfer efficiency.

Fig.13 shows that as the feature size of the packing increases,characteristic diameterdeof the droplet gradually decreases,and uniformity index m increases continuously,indicating that the diameter of the droplet decreases,and the droplet size distribution.The narrowing and the uniformity of the distribution improve.A possible reason is that as the characteristic size of the packing increases,the shearing force of the liquid becomes larger,such that more large droplets are sheared into small droplets by the packing.Although the number of droplets becomes larger,the droplets’ overall diameter is reduced.Thus,the droplet diameter distribution becomes smaller,and the uniformity is improved.However,the increase in the size of the packing features when rotational speed and initial velocity of the liquid are constant prolongs the residence time of the liquid in the packing and increases the degree of fluid breakage,droplet velocity,and the geometry in the cavity region.The size is reduced,such that the flight time of the droplet is reduced.The occurrence of droplet coalescence is reduced.Thus,once the droplet diameter when flying out of the packing is determined,the droplet diameter distribution improves.

Fig.11.Variation of droplet size probability density distribution with packing feature size.

Fig.12.Comparison of experimental and simulated values in the R-R distribution model for each packing feature size.

Fig.13.Effect of feature size of packing on fitting parameters de and m.

4.8.Droplet velocity

The study of droplet velocity in RPB can lay a theoretical foundation for the study of the degree of turbulence and the residence time of droplets,which is of great significance for gas–liquid mass transfer and heat transfer.The droplet velocity in the RPB can be divided into three types: droplet combining speedVH,tangential velocityVT,and radial velocityVR.Tangential velocity and radial velocity are components of combined velocity.

Fig.14 is a velocity diagram of the liquid in a countercurrent RPB under certain conditions.The closer the liquid is to the outer edge of the packing,the greater the droplet velocity.Fig.15 shows the change of droplet size,tangential velocity,and radial velocity of the feature size of the packing.As packing size increases,the three speeds of the droplet increase.As characteristic size of packing increases,centrifugal force experienced by the liquid increases,and droplet velocity increases.In addition,droplet merging speed and tangential velocity vary widely,and their values are similar and much greater than radial velocity.

Fig.14.Velocity field cloud map(N=1200 r·min-1,u0=1 m·s-1,and R=0.101 m).

Fig.15.Effect of packing feature size on droplet collapse speed,radial velocity and tangential velocity.

5.Conclusions

In this paper,the counter-rotating packed bed is taken as the research subject.The main factors affecting the flow of liquid in the RPB are analyzed.The PIV technology is used to visually observe the liquid in the rotating bed of sieve packing under different feature sizes.The VOF multiphase flow model is adopted by rationally simplifying the physical model.The RSM turbulence model and the slip mesh model are calculated by 2D numerical simulation.Flow characteristics of the liquid under different feature sizes are obtained by comparison of experiments and simulation results.The liquid in the counter-rotating rotating packed bed mainly exists as droplets in the cavity region and as droplet flow and liquid line flow in the packed region.The fluid passes through the packing to become droplets and liquid lines,which increases the gas–liquid contact area and enhances the mass transfer process.As the characteristic size of the packing continues to decrease,droplet flow and liquid line flow gradually appear in the cavity region.The average diameter of the droplet decreases as the characteristic size of the packing increases,decreases as the rotational speed increases,and increases as the initial velocity of the liquid increases.The data fitting correlation shows that the characteristic size of the sieve packing has the most substantial influence on the average diameter of the droplet.The sieve packing has a shearing effect on the droplets.The larger the radial thickness of the filler is,the faster the rotation speed,and the stronger the shearing effect; the simulated value and predicted value are within ±15%.The droplet size distribution in the counter-rotating packed bed conforms to the R-R distribution.When the characteristic size of the packing increases,droplet characteristic diameterdedecreases,and uniformity indexmincreases,indicating that the droplet size distribution gradually improves.Dropletting speed,radial velocity,and tangential velocity gradually increase with the increase of the packing size.After the droplet reaches the cavity,its velocity decreases with the continuous movement of the droplet.

Declaration of Competing Interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: This work was supported by the Specialized Research Fund for Sanjin Scholars Program of Shanxi Province (201707),Key Research & Development Plan of Shanxi Province(201903D321059),Shanxi Scholarship Council of China(HGKY2019071).

Acknowledgements

This work was supported by the Key Research & Development Plan of Shanxi Province (201903D321059) and Shanxi Scholarship Council of China (HGKY2019071).