COMPARISON OF DIFFERENT COLLECTION EFFICIENCY MODELS FOR VENTURI SCRUBBERS USING A GENERAL

SOFTWARE

N.D. Charisiou, N. Argiropoulos, K. Papageridis and M.A. Goula1

Laboratory of Alternative Fuels and Environmental Catalysis (LAFEC)Department of Pollution Control Technologies (PCT)

Technological Educational Institute of Western Macedonia (TEI WM)Kozani, Koila, 50100, Greece

Email: mgoula@teikoz.gr1

ABSTRACT

Venturi scrubbers are used widely for removing particles from gases because of their many attractive features: they remove sub-micrometer particles efficiently; they are compact and simple to build, so that initial investment costs are small in comparison to other types of particle collection devices; and they function well in problematic situations such as hot or corrosive atmospheres and when sticky particles must be collected.

A typical venturi scrubber consists of a converging section, throat section into which the scrubbing liquid is injected, and relatively longer diverging section where much of the energy recovery and particulate collection occurs. At the scrubber injection position, a high relative velocity between the scrubbing liquid and gas causes atomization of the liquid into a distribution of fine droplets. Impingement of gas upon a pool of liquid causes the atomization and entrainment of liquid drops. The predominant mechanism for particles greater than about 0.3 micron diameter has been shown to be inertial impaction.

The literature contains a number of models to predict venturi scrubber efficiency and pressure drop. These models are useful in optimizing and designing new venturi scrubbers as well as predicting the effects of changing parameters in existing ones. Some models are explicit, analytical expressions that have straightforward solutions. Others are more complex and require numerical solution with a computer. In regards to collection efficiency, among the most widely used are those developed by (i) Calvert et al (1972) and Johnstone et al (1954). A popular model for the calculation of pressure drop is that developed by Young et al (1978).

The purpose of the present work was to develop a generic software that allows the user to calculate the predicted venturi scrubber efficiency and pressure drop using the models mentioned above, over a wide range of operating conditions. It has been designed using MATLAB, as it is easy to use by the untrained, while among others, it allows the use of excel spreadsheets and the production of AutoCad drawings.

KeywordsVenturi scrubbers, Collection Efficiency, Particle Collection

1. INTRODUCTION

In the last four decades, the technical community has expanded its responsibilities to society to include the environment, with particular emphasis on air pollution from industrial sources. One of the most common air pollution abatement devices used are venturi scrubbers (Figure 1). Such systems can be used either for the collection of particulate material from gas streams or for the control of Volatile Organic Compounds (VOCs). The advantages of these systems include high collection efficiencies for relatively small particles and low capital and maintenance costs. The main cost is associated with the operating fans that are used to overcome the venturi’s relatively high pressure drop (Naseh et al, 2006; Pulley, 1997; Silva et al, 2009).

A typical venturi scrubber consists of a converging section, throat section (Figure 2) into which the scrubbing liquid is injected, and relatively longer diverging section where much of the energy recovery and particulate collection occurs. At the scrubber injection position, a high relative velocity between the scrubbing liquid and gas causes atomization of the liquid into a distribution of fine droplets. Impingement of gas upon a pool of liquid can also cause the atomization and entrainment of liquid drops, and this principle is used in several types of commercial venturi scrubbers. Particulate matter is collected on liquid droplets by a number of collection mechanisms operating simultaneously. These include inertial impaction, interception, diffusion, condensation, humidification, and electrostatic precipitation (Table 1). However, the predominant mechanism for particles greater than about 0.3 micron diameter has been shown to be inertial impaction (Miller, et al, 1989; Rudnick et al, 1986; Wang et al, 2004; Yung et al, 1978).

Important process variables that affect particle capture include the particles size, the size of liquid droplets, and the relative velocity of the particle and the liquid droplets, with particle size being the most important parameter. In general, larger particles are easier to collect than smaller ones. The key to effective particle capture in a wet scrubber is creating a mist of tiny droplets that act as collection targets: usually, the smaller the droplet and the more densely the droplets are packed, the better the ability to capture smaller-sized particles. Particle capture generally improves with higher energy systems because energy is required to produce the mist of tiny droplets. Also, a high relative velocity between particles and liquid droplets (the particles are moving fast compared

FIGURE 1: Typical Venturi scrubber (Source: Cooper & Alley, 2004)

FIGURE 2: Cross section of a Venturi throat

(Source: Adopted from Theodore, 2008)

to the liquid droplets) promotes particle collection. For gaseous pollutant collection, the pollutant must be soluble in the chosen scrubbing liquid. In addition, the system must be designed to provide good mixing between the gas and liquid phases, and enough time (residence time) for the gaseous pollutants to dissolve.

Other important considerations for both particulate and gaseous pollutant collection are the amount of liquid injected into the scrubber per given volume of gas flow (referred to as the liquid-to-gas ratio) and the removal of any entrained liquid droplets. The liquid-to-gas ratio is important to provide sufficient liquid for effective pollutant removal. Also, the system must be designed to remove entrained mists, or droplets, from the cleaned exhaust gas stream before it leaves the stack. If not removed, the "captured" pollutants could be emitted from the stack.

TABLE 1: Particle collection mechanisms in venturi scrubbers

Mechanism ExplanationImpaction Particles too large to follow gas streamlines around a

droplet collide with it.Diffusion Very tiny particles move randomly, colliding with

droplets because they are confined in a limited space.Direct interception An extension of the impaction mechanism. The

center of a particle follows the streamlines around the droplet, but a collision occurs if the distance between the particle and droplet is less than the radius of the particle.

Electrostatic attraction Particles and droplets become oppositely charged and attract each other.

Condensation When hot gas cools rapidly, particles in the gas stream can act as condensation nuclei and, as a result, become larger.

Centrifugal force The shape or curvature of a collector causes the gas stream to rotate in a spiral motion, throwing larger particles toward the wall.

Gravity Large particles moving slowly enough will fall from the gas stream and be collected.

The literature contains a number of empirical models to predict venturi scrubber efficiency and/ or pressure drop, that are useful in optimizing and designing new venturi scrubbers as well as predicting the effects of changing parameters in existing ones. For the calculation of collection efficiency, some of the most popular models are those developed by Johnstone et al (1954), Calvert (1972), Boll (1973), Young et al (1977) and Concalves et al (2004). For the calculation of pressure drop the models developed by Calvert (1970), Boll (1973), Azzopardi (1991) and Pulley (1997) are amongst the most widely used.

Some of the models mentioned above are explicit, analytical expressions that have straightforward solutions. Others are more complex and require numerical solution with a computer. A common feature in these models is that although most start from firm scientific concepts, they give only qualitative results when predicting collection efficiencies or pressure drops. The interaction of particulate matter having a given particle size distribution with water droplets having another size distribution is not easy to express in quantitative terms. As a result of this complexity, experimentally determined parameters are usually required in order to perform engineering calculations (Theodore, 2008). Thus, caution should be exercised when using these models outside

the range of data used to develop them (Miller et al, 1989). Another factor then needs to be taken into consideration is that few data have been available to confirm model predictions, so model evaluation has been difficult (Rudnick et al, 1986; Silva A.M. et al, 2009).

The purpose of the present work was to develop a generic software that will allow its users to calculate the venturi scrubber collection efficiency using one of the following models: (i) Calvert et al (1972), and Johnstone et al (1954). For the calculation of pressure drop, the model developed by Yung et al (1977) was incorporated into the software. These models were chosen based on an extensive literature search, which revealed that to this day, they remain amongst the most widely used for design purposes. The development of such a software is a necessary task mainly because although one may find some excellent textbooks regarding the design of air pollution control technologies (indicatively, Cooper and Alley, 2004; Wang et al 2004; Theodore, 2008), comparable software are absent (Charisiou et al, 2011). Thus, it is hoped that the software developed herein will prove a useful weapon in the arsenal of educators and/or students of air pollution abatement technologies.

2. SOFTWARE DEVELOPED

2.1 Collection efficiency2.1.1 Johnstone’ model One of the more popular and widely used collection efficiency equations is that originally

suggested by Johnstone et al (1954).

(1)

where η is the collection efficiency, Kp is the inertial impaction parameter (dimensionless), R the liquid-to-gas ratio (gal/1000 acf or gpm/1000 acfm) and k the correlation coefficient, the value of which depends on the system geometry and operating conditions (typically 0.1–0.2 acf/gal). The inertial impaction parameter (Kp) is given by Equation 2, where dp the particle diameter (ft), ρp the particle density (lb/ft3), Vt the throat velocity (ft/s), μG the gas viscosity (lb/ft-s), dd the mean droplet diameter (ft) and C the Cunningham correction factor (dimensionless). The mean droplet diameter (dd) for standard air and water in a venturi scrubber is given by the Nukiyama–Tanasawa relationship, shown in Equation 3. The overall collection efficiency of the system can be calculated using Equation 4, where Md is the weight percent of the particles of a given diameter.

(2), (3) (4)

2.1.2 Calvert’s model

As in many of the available models for the design of venturi scrubbers, the Calvert et al

(1972) model, is based on the prediction of the penetration (Ptd) for a given particle diameter.

Penetration is defined as the fraction of particles (in the exhaust stream) that passes through the

scrubber uncollected. Penetration is the opposite of the fraction of particles collected (i.e. collection

efficiency, ηd), and is expressed as shown in Equation 5. The total penetration can be calculated as

shown in Equation 6.

(5), (6)

According to Calvert et al (1972), the penetration can be calculated by the following Equation:

(7)

where QL and QG are the liquid and gas volumetric flow rates respectively (dimensionless), VG is the gas velocity at the throat (cm/s), ρL is the liquid density (g/cm3), μG the gas viscosity (poise), and f is a correlative parameter that ranges from 0.2 to 0.7. It should be noted that that for the correlation parameter (f), Cooper and Alley (2004), suggest that the value 0.25 should be used for hydrophobic particles, while 0.5 should be used for hydrophilic particles. The inertial impaction parameter (Kp) is given by the following Equation (please note that the first part in Equation 8 is identical to Equation 2 presented above):

(8)

with dp in cm, ρp in g/cm3, Vp,d the particle velocity relative to the droplet velocity, in cm/s (thus in effect it equals Vt), μG in poise, ρw the density of water (in g/cm3) and da the particles aerodynamic diameter (in cm). The mean droplet diameter (dd) for standard air and water in a venturi scrubber, is given by another form of the Nukiyama–Tanasawa relationship (in μm) as follows:

(9)

where σ the liquid surface tension (dynes/cm), and μL

the liquid viscocity (poise).

2.2 Pressure drop

The pressure drop in venturi scrubbers can be calculated by the model developed by Young

et. al. (1977) by the following equation:

(10)

where ΔP the pressure drop (dyne/cm

2

), and Χ the dimensionless throat length, which can be

calculated by Equation 11 (where lt

the venturi throat length, in cm). The drag coefficient, CD

for

droplets with Reynolds numbers, Re, from 10 to 500 can be obtained by Equation 12 (Cooper and

Alley, 2004). The Reynolds number can be calculated using Equation 13 (where ρG

the gas density,

in g/cm

3

).

(11), (12), (13)

3. RESULTS AND DISCUSSION

As has been mentioned above, some of the best educational textbooks for air pollution abatement technologies (e.g., Cooper and Alley, 2004; Wang et al 2004; Theodore, 2008), consider the models chosen for the development of the software presented herein, useful in the training of future engineers in the design of venturi scrubbers. Naturally, these models are not without flaws. Further, of the numerous models developed in the past 30 years, some were bound to give more accurate predictions. Thus, a short discussion, comparing the models used in this paper, with other models reported in the literature is warranted.

Calvert et al (1970) presented the first model for pressure drop in venturi scrubbers, however, they neglected wall friction and momentum recovery in the divergent section, so other researchers tried to improve this model. Boll (1973) solved simultaneous equations of drop motion and momentum exchange for variable cross section ducts with acceptable results, except for very high and low liquid to gas ratios, where it did not show agreement with the experimental data. Azzopardi and Govan (1984) considered momentum losses due to accelerating droplets entrained from the film and the interfacial drag between the fast moving core and the slower moving liquid film. However, they had little successes with this procedure (Nasseh et al, 2006). Pulley (1997) carried out various experiments and suggested more effective variables such as drop size, entrainment at liquid injection and entrainment and deposition along the venturi length. He also compared pressure drop predictions from various models (amongst these were the models developed by Young, Boll and Azzopardi) and concluded that the corrected proposed model of Azzopardi et al. (1991) gave a better prediction of pressure drop for a wider variety of data. Goncalves et al (2001) studied a large number of models for the prediction of pressure drop in venturi scrubbers and concluded that all of them must be used with caution.

In regards to collection efficiency, Rudnick et al (1986), vigorously compared the models developed by Calvert et al (1972), Boll (1973) Young et al (1978) and concluded that the model of Yung et al (1978) is probably best for most applications because it is an explicit algebraic expression and gave the best results of the models tested. The model of Calvert et al. (1972), while also an explicit algebraic expression (and thus easy to use), is very dependent on the choice of the correlative parameter, f, and thus should be used with caution. One of the latest attempts at modeling the collection efficiency was undertaken by Concalves et al (2004) who studied the atomization of the liquid jets injected transversally to a gas stream in a venturi scrubber. A mathematical model was developed to predict the trajectory, breakup and penetration of the liquid jets. With this model for liquid jet dynamics, Concalves et al (2004) calculated the spatial distribution of droplets for the case where liquid was injected through a single orifice in a rectangular venturi scrubber.

The software presented herein (Figure 3) enables the calculation of a venturi scrubber’s efficiency and pressure drop for the theoretical models described in section 2. The parameters that

are necessary in order to carry out the design are the following: (i) Gas and liquid characteristics (temperature and pressure - viscosity and density are calculated by the software), (ii) Particle characteristics (particle distribution and density) and (iii) Process characteristics (volumetric flow rate and particle loading). Further, when using the Johnstone et al (1954) model the user must choose a value for the correlation coefficient k (ranges between 0.1–0.2 acf/gal), while for the Calvert et al (1972) model the user must know/decide whether the particles that need removing are hydrophobic or hydrophilic, as this determines the value of the correlation parameter, f (0.25 and 0.5 respectively).

Figure 3: Graphic interface of the software developed – Calvert et al (1972) model

FIGURE 4: Efficiency as a function of the liquid-to-gas ratio P=1atm, T=80oF, ρL=62.22lb/ft3, μL=0.86cp, σ=71.7dynes/cm, VG=32.68m/s, daj=2.5, 7.5, 15, 35, 60, 80μm, mj=8, 18, 23, 23, 20, 8%f=0.5 (Calvert model)k=0.2acf/gal (Johnstone model)

FIGURE 5: Efficiency as a function of the gas velocity at the Venturi throatP=1atm, T=80oF, ρL=62.22lb/ft3, μL=0.86cp, σ=71.7dynes/cm, f=0.5, QL/QG=1L/m3, da=2.5, 7.5, 15, 35, 60, 80μm,mj=8, 18, 23, 23, 20, 8%f=0.5 (Calvert model)k=0.2acf/gal (Johnstone model)

Figure 4 presents the predicted efficiency as a function of the the liquid-to-gas ratio for the models included in the software that was developed in the present work. It can be observed that the Johnstone model predicts much higher efficiencies even at low ratio values. Moreover, the difference between the lowest and highest ration values is small, compared to the predictions obtained using Calvert’s model. Figure 5, presents the predicted efficiency as a function of the gas velocity at the venturi throat, In essence, the Johnstone et al (1954) model fails to make any predictions (predictions close to 100%) regardless of the changes in the throat velocity. This may be attributed to the large particle diameters chosen for these diagrams. This is better demonstrated in Figure 6, which shows a curvature in the Johnstone model for particles up to 2μm, while Calvert’s model reaches peak values at 7μm. It should be noted that in all three Figures, Calvert et al (1972) model predictions are a lot closer to the curve one would normally expect. Figure 7 shows the predicted efficiency as a function of the the liquid-to-gas ratio, Figure 8, presents the predicted efficiency as a function of the gas velocity at the venturi throat, and Figure 9 the efficiency as a function of particle diameter, in Calvert’s model, for different correlative parameter (f) values, demonstrating the model’s dependence on it. This is in accordance to the available literature (see above) and emphasises the need for caution when using the model.

FIGURE 6: Efficiency as a function of particle diameter P=1atm, T=80oF, ρL=62.22lb/ft3, μL=0.86cp, σ=71.7dynes/cm, VG=32.68m/sf=0.5 (Calvert model)k=0.2acf/gal (Johnstone model)

FIGURE 7: Efficiency as a function of the liquid-to-gas ratio – Calvert’s modelP=1atm, T=80oF, ρL=62.22lb/ft3, μL=0.86cp, σ=71.7dynes/cm, VG=32.68m/sda=2.5, 7.5, 15, 35, 60, 80μm,mj=8, 18, 23, 23, 20, 8%

4. CONCLUSIONS

In concluding, the software presented herein offers an easy way to calculate the efficiency and pressure drop of a venturi scrubber. Some of the most widely used theoretical models for venturi design have been incorporated in this software. Thus, a comparison of the results predicted by the models with experimental results, will allow the user to either determine which model provides the most accurate predictions or to choose the configuration most adapted to an operating condition. However, in its current state, the software will prove more useful to educators and/or students of air pollution abatement devices.

A number of improvements could be done in the future to make the software more efficient by:

(i) Allowing the user to enter the desired collection efficiency or pressure drop in order to obtain the proposed liquid to gas ratio and/or gas entrance velocity,

(ii) Introducing additional models for the calculation of collection efficiency (e.g. those developed by Boll (1973), Young et al (1977), Concalves et al (2004)),

(iii) Introducing additional models for the calculation of pressure drop (e.g. those developed by Boll (1973), Pulley (1997)).

Furthermore, one may also try to incorporate additional wet scrubbing configurations (e.g. spray towers).

REFERENCES

1. Azzopardi B.J. and A.H. Govan (1984), ‘The modeling of Venturi scrubbers’ Filtration and Separation, Vol. 23, pp. 196–200.

2. Azzopardi B.J., S.F.C.F. Teixeira, A.H. Govan and T.R. Bott (1991) ‘An improved model for pressure drop in Venturi scrubbers’, Transactions of the Institute of Chemical Engineers, B69, pp. 55–64.

FIGURE 8: Efficiency as a function of the gas velocity at the Venturi throat – Calvert’s modelP=1atm, T=80oF, ρL=62.22lb/ft3, μL=0.86cp, σ=71.7dynes/cm, QL/QG=1L/m3, daj=2μm

FIGURE 9: Efficiency as a function of particle diameter – Calvert’s modelP=1atm, T=80oF, ρL=62.22lb/ft3, μL=0.86cp, σ=71.7dynes/cm, QL/QG=1L/m3, VG=50m/s

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