Influence of Droplet Size Distribution on Liquid Dispersion in a Venturi

Article pubs.acs.org/IECR

Influence of Droplet Size Distribution on Liquid Dispersion in a Venturi Scrubber: Experimental Measurements and CFD Simulation Vádila G. Guerra,*,† Ana Elisa Achiles,† and Rodrigo Béttega† †

Department of Chemical Engineering, Federal University of São Carlos, Rodovia Washington Luiz, km 235, 13565-905 São Carlos, São Paulo, Brazil ABSTRACT: Venturi scrubbers provide highly efficient removal of particles from dust-laden gases. A uniform distribution of droplets improves the collection efficiency. Most computational models used to predict the dispersion of liquid in scrubbers employ the Boll correlation to calculate the mean droplet size. Given the lack of studies considering the effect of droplet size distribution on the liquid dispersion in Venturi scrubbers, the present work provides an experimental and numerical evaluation of this effect. Experimental measurements of droplet size distribution and liquid dispersion were made under different conditions. The fluid dynamic was simulated with ANSYS Fluent 14.0 software, using a discrete phase trajectory model. The simulations were performed with droplet size distributions measured experimentally and predicted using parameters from literature. The results for the simulated liquid dispersions were in agreement with the experimental data and indicated a strong dependence of the liquid distribution in the scrubber on the parameter values used in the droplet size distribution model.

1. INTRODUCTION Among the various systems available for cleaning gas streams, the Venturi type scrubber is extensively used in industrial applications due to its high efficiency in removing particles in a wide range of granulometric sizes, including the respirable dust fraction that is most damaging to health. The equipment essentially consists of a converging section, a constriction known as the throat, and lastly a diverging section. The operating principle of Venturi scrubbers involves the introduction of liquid, usually through nozzles in the scrubber throat. The injected liquid entering the system in the form of a jet that atomizes in contact with the high velocity gas, forming numerous droplets that collect the particles from dust-laden gas. The jet penetrates in the Venturi throat as a continuous body of liquid that becomes curved, due to the drag force, and then rapidly disintegrated in droplets. The atomization process is a complex phenomenon influenced by operational conditions and characteristics of the jets, such as liquid−gas flow rate and jet penetration, and affects the droplet size and liquid distribution. The recently formed droplets are located in the proximity of the jet trajectory, and then they are dragged and dispersed by turbulent diffusion. The efficiency of a scrubber is affected by the characteristics of particles and the droplets formed by atomization, such as size, quantity, relative velocity, and spatial distribution. The collection performance is largely determined by the uniformity of the liquid distribution within the scrubber.1 The importance of the droplet distribution in determining the performance of Venturi scrubbers was reported in early studies of this device.2 The droplet size and distribution is influenced by various operational parameters, especially the gas velocity in the throat and the liquid/gas ratio. Design features such as the throat length and diameter as well as the number and location of liquid © XXXX American Chemical Society

injection nozzles also have an important influence on liquid dispersion and particle collection efficiency. In industrial applications, Venturi scrubbers have several nozzles for liquid injection, and the correct configuration of these nozzles can improve droplet/particle contact and hence increase the collection efficiency. Guerra et al.3 reported that the number of liquid injection inlets and the gas/liquid ratio not only affected the initial dispersion of the liquid in the device but also were important in determining the mean size of the droplets generated. The Sauter mean diameter increased as the number of operating inlets was increased, despite the fact that this effect was not predicted by the correlations available in the literature. Most studies of the dispersion of liquids in scrubbers, as well as models for its prediction, consider a fixed arrangement of liquid injection nozzles and do not allow for changes in the size distribution of the droplets under different operating conditions.4−10 There are limited data available concerning the influence of the injection configuration on the dispersion of liquid in Venturi scrubbers.1,11 Ananthanarayanan and Viswanathan11 evaluated the effect of the arrangement of injection nozzles on the liquid dispersion in a rectangular Venturi scrubber. The flows of the liquid and gas phases were simulated using Fluent software, and a discrete phase model was used in an Eulerian−Lagrangian approach to study the behavior of the droplets. The droplet distribution was considered monodisperse, and the mean diameter was calculated using the equation of Boll et al.12 According to Shyan and Received: Revised: Accepted: Published: A

September 27, 2016 January 27, 2017 January 30, 2017 January 30, 2017 DOI: 10.1021/acs.iecr.6b03761 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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Industrial & Engineering Chemistry Research

Figure 1. Dimensions of modular Venturi scrubber used in the experiments: (a) front view, (b) side view.

Table 1. Experimental Conditions Evaluated experiment

number of nozzles

Vg (m/s)

Vj (m/s)

L/G (L/m3)

E-1 E-2 E-3 E-4 E-5

2 2 3 3 4

64 74 64 74 64

4.3 7.5 4.3 5.0 4.3

0.10 0.15 0.15 0.15 0.20

operating under different conditions. The variables studied were the pressure and volumetric fraction of each phase. The simulations were performed using ANSYS Fluent software and a multiphase VOF (volume of fluid) Eulerian model. The results indicated that for the same liquid/gas ratio, the number of fluid injection nozzles did not affect the pressure drop, but rather, they influenced the distribution of the liquid fraction within the device, mainly due to altered penetration of the jets. One of the limitations of the VOF model is that it does not take account the droplet size distribution in determining the distribution of the liquid fraction. The droplet size distribution affects the dispersion of the liquid, because larger droplets tend to maintain their original trajectories, while smaller droplets can easily change their trajectories. In the work of Fernandez Alonso et al.,13 it was

Figure 2. Apparatus used to measure the liquid dispersion.

Viswanathan,6 the liquid flow distribution is a strong function of the polydispersity of the droplets, with the finer droplets tending to show greater lateral dispersion than the coarse droplets in the throat of the scrubber, resulting in a more uniform liquid flow distribution and better coverage of the throat. Guerra et al.1 used experimental optical imaging techniques and CFD simulations to study the fluid dynamics of the gas and liquid phases in the core of the throat of a Venturi scrubber

Figure 3. Measurements of liquid dispersion: (a) general view of the test section; (b) location of the planes and lines along which measurements were made. B

DOI: 10.1021/acs.iecr.6b03761 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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Figure 4. Detail of the test section to permit laser analysis of droplets.

Figure 5. Computational mesh.

found that the Rosin−Rammler function (eq 1) was most suitable for predicting the droplet diameter distribution in a Venturi scrubber. ⎛ ⎛ D ⎞n ⎞ 1 − ϕ = exp⎜⎜ −⎜ d ⎟ ⎟⎟ ⎝ ⎝ χ⎠⎠

(1) Figure 6. Experimental and Rosin−Rammler model droplet size distributions: (a) Experiment E-1; (b) Experiment E-3.

In eq 1, ϕ represents the mass fraction of droplets with diameters smaller than Dd, and χ and n are characteristic parameters. Parameter χ is the mean Rosin−Rammler diameter and represents the diameter at which 63.2% of the total liquid mass is present in droplets of smaller diameter, and n is a spread parameter used to adjust the width of the size distribution. On the basis of the study of Fernandez Alonso et al.,13 the models for prediction of liquid dispersion proposed by Gonçalves et al.7 and Ahmadvand and Talaie9 used the Rosin−Rammler size distribution with a value of n equal to 2.15 and calculation of χ using correlation with the Sauter mean diameter (D32) and Gamma function (Γ), as shown in eq 2. In these studies, the Sauter mean diameter was determined by the correlation of Boll et al.12 (eq 3), because this provided good agreement with the experimental results of Fernandez Alonso et al.13 ⎛ χ 1⎞ = Γ⎜1 − ⎟ ⎝ D32 n⎠

D32 =

Table 2. Parameters χ and n of the Rosin−Rammler Model, Determined Experimentally and Using eq 2 with Values from the Literature

14

3

χexptl (μm)

nexptl

χlit.a (μm)

nlit.b

E-1 E-2 E-3 E-4 E-5

196.20 140.52 215.15 166.70 145.23

2.18 1.97 1.98 1.95 2.11

89.53 71.16 89.70 71.10 89.98

2.15 2.15 2.15 2.15 2.15

a

With D32 obtained using eq 3 (Boll et al., 1974). bFernandez Alonso et al. (2001).

predicted using the Boll et al.12 equation, and concluded that the correlation did not satisfactorily represent the experimental results, with underestimation of the Sauter mean diameter values. Ahmadvand and Talaie9 evaluated the influence of the spread parameter (n) on the dispersion of liquid in a cylindrical scrubber, using an Eulerian approach and a two-dimensional mathematical model. It was concluded that the distribution parameter

(2)

4.22 × 104 + 5.77 × 103(L /G)1.922 Vg1.602

experiment

(3) 15

In contrast, Costa et al., Guerra et al., and Silva et al. compared their experimental droplet size results with the values C


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Figure 8. Experimental images of liquid jets (a) E-2 and (b) E-4.

particle removal efficiency, and it was concluded that the particle removal efficiency increased at higher liquid and gas flows. The aim of the present work was to evaluate the effect of droplet size distribution on the dispersion of liquid within a rectangular Venturi scrubber operated under different experimental conditions. To this end, analysis was made of experimental data and the results of CFD simulations performed using a discrete particle modeling (DPM) approach.

2. EXPERIMENTAL PROCEDURE The equipment used in the experimental tests was a Venturi scrubber constructed of acrylic modules, with a rectangular cross-section and throat dimensions of 0.027 × 0.040 m. Liquid was injected using a helicoidal impeller pump that transferred water from a reservoir to the first module of the scrubber throat, in which four injection nozzles (0.001 m diameter) were installed, one in each wall of the throat. A schematic illustration of the equipment and its main dimensions are shown in Figure 1. The dispersion of the liquid was measured by an isokinetic sampling method previously used successfully by Viswanathan et al.16 and Gonçalves et al.7 In this procedure, an acrylic test section was installed between the throat and the diffuser. This test section contained a probe through which air and part of the droplets that flowed through the throat were sucked into a small aluminum cyclone containing a column of silica gel on the top. The purpose of the cyclone was to separate the biphasic flow and retain the liquid. The liquid was collected into the cyclone for a period of time and then weighed to determine the liquid mass flow. The suction provided by a pump was adjusted using a flow meter so that the suction rate was equal to the air velocity within the throat. Figure 2 shows a general view of the setup for

Figure 7. Experimental and simulation results for static pressure along the Venturi scrubber: (a) E-1; (b) E-3; (c) E-4.

n of the Rosin−Rammler function could not be considered constant and that it depended on the operational conditions of the equipment. Majid et al.10 evaluated the effectiveness of a Venturi scrubber for the removal of solid particles from a gas stream using CFD simulations in a Lagrangian−Eulerian approach, performed with ANSYS CFX software. Analysis was made of the performance of the Venturi scrubber under different conditions of gas velocity in the throat of the Venturi, volume fraction, droplet size, and D


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Figure 9. Simulated concentrations of liquid (kg/m3) within the gas phase for operational condition E-1, considering different distribution parameters: (a) simulation results using χexptl and nexptl; (b) simulation results using χlit. and nlit..

The droplet size distribution was measured experimentally under different operational conditions by laser diffraction using a Spraytec system (Malvern Instruments model RTS5134). In this device, when the laser light encounters a droplet, part of the light energy is reflected, part is diffracted, and part is absorbed. The diffraction angle is inversely proportional to the size of the droplet, hence enabling the determination of the droplet size distribution in the spray. In this equipment, a 3 mW Helio-Neon laser generator produces laser light at a wavelength of 632.8 nm. The beam of light is expanded by a lens and passes through the spray where a part of the light energy is diffracted at various angles that depend on the size distribution of the droplets in the spray. The lens used in the experimental tests was a 200 mm focal length lens that provided a particle size range, based on median of the particle size distribution, from 5 to 250 μm. The actual range of the instrument is wider than listed (5−250 μm) to accurately measure particles both above and below the median.17 An important attribute of this equipment is that the diffraction parameter generated by the droplets is independent of the droplet position in the light beam. This allows size distribution measurements to be made with droplets moving at high velocity. The accuracy of the instrument typically have better than ±2% over 96% of the particle size distribution. The instruments accuracy tends to decrease at the extremities, or outer 4%, of the particle size distribution.17 The droplet size distribution were done at least two times over a period of time for each experimental condition. One of the problems associated with optical methods is gaining access to the interior flow when its characteristics can not be altered. In order to perform the droplet measurements in situ, a test section was connected after the throat module with liquid injection nozzles, and measurements were made approximately 0.02 m from the injection point. This test section consists of quartz windows that allow the passage of the laser, laminas, and

sampling the droplets, and Figure 3 shows the test section for measuring the liquid dispersion. The liquid dispersion within the throat was evaluated in two planes, one located at a distance of 0.016 m from the liquid injection plane, denoted plane 1, and another at 0.076 m, denoted plane 2, as shown in Figure 3b. In order to sample at different positions on the same transverse plane, the section was constructed so as to enable movement in the vertical and horizontal directions. In these tests, it was decided to only measure the liquid dispersion along the central lines of each plane, X and Y, as illustrated in Figure 3a,b. The dispersion was measured using the mass flows of liquid collected at each point of lines X and Y of the transverse planes shown in Figure 3b. Analysis of the liquid distribution used the normalized flow, (ωnorm.), given by

ωnorm. =

ω local ωaverage

(4)

where ωlocal is the flow measured by the probe in each position, and ωaverage is the flow that would be observed in the throat if there was a uniform distribution of droplets. The value of ωaverage could be obtained by dividing the mass flow of water injected into the scrubber by the area of the transverse section of the throat. The test conditions are provided in Table 1. L/G ratio was calculated considering the total liquid flow rate injected in Venturi scrubber and gas flow rate for each experimental condition. Jet velocity was calculated by Vj =

L Aor ·Nor

(5)

where L is the liquid flow rate, Aor is the area of liquid injection orifice, and Nor is the number of orifices of liquid injection. E


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within Venturi scrubbers.13 The values of the parameters of the Rosin−Rammler model (scattering, n, and mean diameter, χ) were obtained by fitting, for subsequent use in the CFD simulations. The influence of the Rosin−Rammler model parameters on the simulated liquid dispersion was evaluated by varying the values of χ and n according to data reported in the literature. The diameter, χ, was calculated using eq 2, with Sauter mean diameters (D32) obtained using the equation of Boll et al.12 (eq 3). The value of n was considered to be constant at 2.15, as reported by Fernandez Alonso et al.13 and used in the studies of Gonçalves et al.7 and Ahmadvand and Talaie.9 To make visualization of the liquid jet in throat possible, a glass front was used on the throat. The lateral wall was given a black background to improve the contrast of the jet of water. Images were taken using a Sony video camera, model DCR-DVD 403 with a resolution of 3 megapixel.

3. NUMERICAL SOLUTION The CFD simulations adopted a three-dimensional domain based on the geometry of the equipment. Four liquid injection nozzles were located in the throat of the device and the number of simulated injections (depending on the experimental conditions) was varied for each nozzle individually. This enabled the same computational mesh to be used in tests with different numbers of injection nozzles. The computational mesh was constructed considering the dimensions and other geometric characteristics of the equipment (Figure 1). The computational domain included the regions before and after the Venturi throat for avoiding disturbances due to boundary effects near the region of interest. Figure 5 illustrates the computational mesh used. Preliminary tests performed with different mesh configurations were used to establish the degree of refinement and the characteristics of the mesh, considering the computational cost and deviations of the variables found for different meshes. The resulting mesh configuration was stable and had a reasonable computational cost. The hybrid mesh had 1 178 610 cells, with 2 540 298 faces and 333.383 nodes. Hexahedral cells were used in the throat inlet and outlet regions, and tetrahedral cells were used in the throat itself, where the liquid injection nozzles were located (Figure 5). The boundary conditions employed for solution of the model were as follows (Figure 5): • Air inlet (point 1): velocity defined at the face; • Air and liquid outlet (point 2): pressure defined at the face; • Walls of the equipment: no-slip conditions for both fluids. The type of injection used in the simulation was the surface injection (point 3). In this type of injection, a particle stream is released from each facet of the surface. Circular surfaces were created using the dimensions and locations of the injection orifices, as shown in Figure 5. The surfaces were used as sources for injection of the droplets, and they were injected using face normal direction of the surface, with jet velocity (see eq 5), and scale flow rate by face area. The simulations were performed with the commercial ANSYS Fluent 14.0 CFD software. The model parameters were based on the work of Ananthanrayanan and Viswanathan,11 with the exception of the droplet size distribution, which was considered polydisperse and was represented by the Rosin−Rammler model. Ananthanrayanan and Viswanathan11 assumed a monodisperse

Figure 10. Comparison of simulated and experimental liquid flow distributions for condition E-1: (a) line Y of plane 1 (see Figure 3b); (b) line Y of plane 2; (c) line X of plane 2.

slots to remove the liquid film and a compressed air injection system, which keeps the droplets from reaching the quartz windows. Figure 4 shows the illustrative diagram of the test section. The experimental droplet size distribution data were fitted using the Rosin−Rammler model, which has previously been found to be most suitable for describing the droplet distribution F


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Figure 11. Comparison of simulated and experimental liquid flow distributions for condition E-2: (a) line Y of plane 1; (b) line X of plane 1; (c) line Y of plane 2; (d) line X of plane 2.

Figure 12. Simulated liquid concentrations (kg/m3) within the gas phase for operational condition E-3, using different distribution parameters: (a) simulation with χexptl and nexptl; (b) simulation with χlit. and nlit..

4. RESULTS AND DISCUSSION Figure 6 shows the experimentally measured droplet size distributions for conditions E-1 and E-3, together with the fitting of the experimental data using the Rosin−Rammler model. This model provided satisfactory fits to all the experimental data (Table 1), as shown in Figure 6 for conditions E-1 and E-3. The fits therefore enabled determination of the values of the model parameters (χexptl and nexptl). Table 2 shows the values of the Rosin−Rammler model parameters obtained from the experimental fits (χexptl and nexptl),

distribution of droplets with diameter calculated using the equation of Boll et al.12 A Lagrangian discrete particle model (DPM) was used to predict the steady-state dispersion of liquid in the device. The RNG k-epsilon turbulence model was adopted. Pressure−velocity coupling was solved by the SIMPLE method, using second-order upwind discretizations for the moment and turbulence equations. Gravitational effects were ignored in the simulations. For all variables, the convergence criteria were maintained at 10−4, with relaxation parameters in the range 0.2−0.4. G


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Figure 13. Comparison of experimental and simulated liquid flow distributions for condition E-3: (a) line Y of plane 1; (b) line X of plane 1; (c) line Y of plane 2; (d) line X of plane 2.


and Silva et al.,15 it was found that the correlation proposed by Boll et al.12 underestimated the Sauter mean diameters measured experimentally. This resulted in lower mean Rosin− Rammler diameter (χ) values. In the case of the spread parameter (n), Ahmadvand and Talaie9 reported that it should not be considered constant in models for the prediction of liquid dispersion in scrubbers. In the present work, the values of n were similar for the different operating conditions and were also close to the value of 2.15 found by Fernandez Alonso et al.13

together with the Rosin−Rammler diameter values (χlit.) calculated using eq 2, with Sauter mean diameters (D32) obtained using the equation proposed by Boll et al.12 (eq 3), assuming the dispersion parameter (nlit.) to remain constant at 2.15. It can be seen from Table 2 that the Rosin−Rammler diameters measured experimentally were significantly larger than those obtained using eq 2 with Sauter mean diameters calculated according to eq 3. In the studies of Costa et al.,14 Guerra et al.,3 H


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Figure 15. Simulated liquid concentrations (kg/m3) in the gas phase for operational condition E-5, considering different distribution parameters: (a) simulation using χexptl and nexptl; (b) simulation using χlit. and nlit..

throat a few centimeters after injection. This was due to the greater inertia of the larger droplets, which enabled them to maintain their original trajectories and reach the central throat region in higher concentrations. The smaller droplets (Figure 9b) were more evenly distributed in the throat of the scrubber because they were more easily dispersed. This behavior was maintained beyond several centimeters from the injection plane, as can be seen for plane 2 in Figure 9a,b. Figure 10 shows a comparison of the experimental liquid distribution for condition E-1, measured along the lines X and Y in planes 1 and 2 (Figure 3), and the distributions predicted by the model using distribution parameters χexptl and nexptl, and χlit. and nlit.. The liquid distributions predicted by the model were normalized using the average concentrations for the planes evaluated, namely the average simulated concentrations in the x−y planes located 0.016 m (plane 1) and 0.076 m (plane 2) from the injection plane. Differences were clearly evident for these conditions. The flow for line X, which was located 0.016 m from the injection plane, was zero in all cases (not shown). It can be seen from Figure 10 that close agreement was obtained between the experimental values and the values predicted by the model using the parameters χexptl and nexptl. The dispersion of droplets in the plane close to the injection (plane 1) was not uniform (Figure 10a), because the entrainment of the liquid caused curvature of the jets, so that the liquid did not reach the central throat region and two high liquid concentration peaks were obtained in the vicinity of the walls near the injection. As the droplets advanced toward positions (plane 2) more distant from the injection plane, the liquid distribution became more uniform and occupied the central region of the throat. This behavior was evident for both the experimental and simulated data and is illustrated for the different operating conditions in Figures 11, 13, 14, and 16. It can also be seen from Figures 11, 13, 14, and 16 that despite the distinct behavior in the plane close to the injection (plane 1), after several centimeters from the injection plane (at plane 2), closer agreement was found between the liquid dispersions predicted by the models that used the experimental and literature Rosin−Rammler parameters.

Figure 7 shows the static pressure along the length of the Venturi scrubber (Z axis) for experimental conditions E-1, E-3, and E-4. Independent of the number of nozzles, the simulation results showed good agreement with the experimental values. Comparison of the pressures at the inlet of the device (z = 0 m) under the different conditions showed that higher flows of liquid or gas increased the pressure drop in the scrubber. This behavior was in agreement with the findings of Guerra et al.,1 who used an Eulerian approach for system simulation. Figure 8 shows the throat of the scrubber with the injection of liquid through 2 and 3 nozzles (E-2 and E-4, respectively). The fluid entered the throat as a jet that encountered the high velocity air stream and deviated, disintegrating into droplets. Both the curvature of the liquid trajectory and the droplet size were dependent on the operational conditions, with the liquid and gas flows affecting the liquid dispersion in the scrubber.3 Figures 9, 12, and 15 illustrate the simulated liquid dispersion (in kg/m3) in the throat, for conditions E-1, E-3, and E-5, respectively, where plane 0 shows the dispersion of liquid in the y−z plane located in the center of the throat. The planes denoted plane 1 and plane 2 show the liquid dispersion in the x-y planes located along z at 0.016 and 0.076 m from the injection plane, as shown in Figure 3b. The results presented in Figures 9a, 12a, and 15a were obtained by fitting the Rosin−Rammler size distribution parameters based on the experimental results (χexptl and nexptl). Figures 9b, 12b, and 15b show the liquid dispersion considering the Rosin−Rammler distribution parameters found in the literature (χlit. and nlit.), as shown in Table 2. It can be seen that the simulations satisfactorily predicted the entrainment of the liquid entering the throat of the scrubber, with curvature of the liquid jet similar to the behavior shown in Figure 8. Comparison of panels a and b in Figure 9 reveals that the liquid dispersion was significantly influenced by the mean droplet size, obtained from the Rosin−Rammler model. For condition E-1 (Table 2), the mean experimentally measured sizes of the droplets were approximately 2 times larger than the droplet sizes obtained using eqs 2 and 3. In Figure 9a, it can be seen that there was a greater liquid concentration in the central region of the I


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Although the model was able to satisfactorily predict the experimental measurements, it is important to note that it did not predict the atomization of the liquid, because it was assumed that the liquid emerged from the injection nozzles as droplets, when in practice the liquid entered the scrubber as a jet that broke up into droplets. The model did not take into consideration the coalescence of the droplets or the reatomization of liquid deposited on the walls as a film (because it was assumed that all droplets reaching the walls were captured). It is important to highlight that these phenomena would affect liquid dispersion throughout the scrubber. In terms of the number of liquid injection nozzles, observation of Figures 9−16 reveals that a greater number of nozzles significantly affected the initial droplet dispersion, with an improved liquid distribution near the injection plane. Such behavior can be seen by comparing Figures 11 and 14, corresponding to conditions E-2 and E-4, where the L/G ratios were the same but the liquid was injected through two or three nozzles, respectively. Figures 11c and 14c show that the addition of a nozzle resulted in greater liquid flow and dispersion along line X, reflecting better coverage of the throat by the liquid. Guerra et al.1 also reported that the configuration of the injection nozzles influenced the dispersion of liquid in the throat of the equipment. There was a substantial difference between the liquid dispersions obtained using the experimental parameter values (χexptl and nexptl, Figure 13a,b) and the literature values (χlit. and nlit., Figure 14a,b). Under conditions E-3 and E-4, the L/G ratios were the same, and the liquid was injected through three nozzles. The liquid dispersion predicted by the model using the experimental distribution parameters exhibited a greater flow of droplets in the central region of the throat. In the case of the dispersion predicted using the literature parameters, with smaller mean droplet size, there was a greater flow of droplets in the wall regions near the liquid injection.

It is important to point out that the greater dispersion of liquid in the central region of the scrubber for the larger droplets did not reflect better operational conditions for the collection of particles, because for the same liquid flow, smaller droplets were present at higher number concentrations and provided a greater surface area for the collection of particles. However, the results demonstrated that the droplet size distribution had a significant influence on the liquid distribution near the injection plane.

5. CONCLUSIONS The computational model was able to satisfactorily predict the profiles of pressure and liquid dispersion within the Venturi scrubber, and good agreement was obtained with the experimental results. The droplet size distribution had a significant influence on liquid dispersion near the injection plane (at plane 1, located 0.016 m from the injection plane). This influence was revealed by the different liquid dispersion profiles obtained, comparing the injection of droplets considering Rosin−Rammler size distributions obtained experimentally and using literature parameter values. The progression of the droplets to planes more distant from the injection plane (such as plane 2, located 0.076 m from the injection plane) was associated with a uniform distribution of liquid in the throat section, and the difference between the liquid dispersions obtained using the experimental and theoretical Rosin−Rammler distributions was reduced.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. ORCID

Vádila G. Guerra: 0000-0002-0096-6329 Notes

The authors declare no competing financial interest. J


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(13) Fernandez Alonso, D.; Gonçalves, J. A. S.; Azzopardi, B. J.; Coury, J. R. Drop size measurements in Venturi scrubbers. Chem. Eng. Sci. 2001, 56, 4901. (14) Costa, M. A. M.; Henrique, P. R.; Gonçalves, J. A. S.; Coury, J. R. Droplet size in a retangular Venturi scrubber. Braz. J. Chem. Eng. 2004, 21, 335. (15) Silva, A. M.; Teixeira, J. C. F.; Teixeira, S. F. C. F. Experiments in large scale Venturi scrubber. Part II. Droplet size. Chem. Eng. Process. 2009, 48, 424. (16) Viswanathan, S.; Gnyp, A. W.; St. Pierre, C. C. Examination of gas flow in a Venturi scrubber. Ind. Eng. Chem. Fundam. 1984, 23, 303. (17) Malvern/Insitec. Technical Specifications EPCS. Malvern Instruments: San Ramon, CA, 2001.

ACKNOWLEDGMENTS The authors are grateful to CNPq for the financial support given to this work.

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NOMENCLATURE Aor = Area of liquid injection orifice D32 = Sauter mean diameter (μm) Dd = Rosin−Rammler droplet distribution diameter (μm) L = Liquid flow rate (m3/s) L/G = Liquid to gas flow ratio (L/m3) Nor = Number of orifices n = Spread parameter of the Rosin−Rammler model (−) nexptl = Experimental spread parameter of the Rosin−Rammler model (−) nlit. = Literature spread parameter of the Rosin−Rammler model (−) Vg = Gas surface velocity in the Venturi scrubber throat (m/s) Vj = Liquid injection jet velocity (m/s) X = Axis X (m) Y = Axis Y (m) Z = Axis Z (m) ϕ = Mass fraction of droplets with diameter smaller than Dd Γ = Gamma function ω = Liquid mass flow (kg/s) χ = Mean Rosin−Rammler distribution diameter (μm) χexptl = Experimental mean diameter of the Rosin−Rammler distribution (μm) χlit. = Literature mean diameter of the Rosin−Rammler distribution (μm)

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REFERENCES

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Influence of Droplet Size Distribution on Liquid Dispersion in a Venturi

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