Journal of Chemical Engineering and Environment, Vol. 2, No. 2, pp. 67-71, 2003 Copyright © 2002 Teknik Kimia UNSYIAH

ISSN 1412-5064

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Numerical Prediction of Cyclone Pressure Drop

T. G. CHUAH†, JOLIUS GIMBUN, THOMAS S. Y. CHOONG, and A. FAKHRU’L-RAZI Department of Chemical and Environmental Engineering, Faculty of Engineering,

Universiti Putra Malaysia 43400 UPM Serdang, Selangor, Malaysia † Correspondence Address: chuah@eng.upm.edu.my

Tel: +603-8946 6288 Fax: +603-8946 7120

Abstract. Cyclones are probably the most commonly used means of separating dust from gases, controlling pollution, collecting particulate product or recovering catalyst particles from fluidised reactors. Cyclone design maybe simple but models use to predict the cyclone pressure drops are not always accurate. An accurate prediction of cyclone pressure drop is very important because it relates directly to operating costs. This paper reviews four empirical models for prediction of cyclone pressure drop, namely Shepherd and Lapple (1939), Casal and Martinez (1983), Dirgo (1985), and Coker (1993). This paper studies and compares the pressure drop prediction models of cyclone of different velocity and temperatures. These four models were compared with experimental result conducted by Patterson and Munz (1989), and Parker et al. (1981). Simulation result shows that the Coker’s model predicts cyclone pressure drop far better than the other three models in different operating temperature. While Shepherd and Lapple model is show a good pressure drop prediction in different inlet velocity so as Dirgo model. Keywords: Cyclone prediction, Cyclone Pressure drop, Gas-solid separators

INTRODUCTION

Cyclones are devices that employ a centrifugal force generated by a spinning gas stream to separate particles from the carrier gas. Cyclones by themselves are generally not adequate to meet stringent air pollution regulations, but they serve an important purpose. Their simple design, low capital cost and their nearly maintenance-free operation make them ideal for use as pre-cleaners for more expensive final control devices such as baghouses or electrostatic precipitators. Cyclones are particularly well suited for high temperature and pressure conditions because of their rugged design and flexible components materials. Cyclone collection efficiencies can reach 99% for particles bigger than 5 µm (Silva et al., 2003), and can be operated at very high dust loading. Cyclones are used for the removal of large particles for both air pollution control and

process use. Application in air pollution includes the control of grain dust, sawdust, and rock dust.

The performance of a cyclone separator depends on several factors including design parameters, such as scaling and dimensions of the cyclone separator, and particle parameters, such as particle density and shape factor. The fluid parameters, such as fluid density and viscosity, and operating parameters, such as the inlet velocity of the fluid into the cyclone and the outlet conditions also affect the cyclone performance.

An accurate prediction of cyclone pressure drop is very important because it relates directly to operating costs. Higher inlet velocities give higher efficiencies for a given cyclone, but this also increases the pressure drop, and a trade off must be made. In this study, pressure drop calculations are performed using Shepherd and Lapple (1939), Casal and Martinez (1983), Dirgo (1985), and Coker (1993) model. These four models were compared with experimental

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result conducted by Patterson and Munz, (1989) for the prediction under different inlet velocity and Parker et al., (1981) for the prediction under different temperatures. In this study, the calculations are carried out numerically using Microsoft Excel spreadsheet.

MODEL DESCRIPTIONS

Selected cyclone design

There are a few different forms of cyclone but the reverse flow cyclone represented in Fig. 1 is the most common design used industrially. The cyclone consists of four main parts: the inlet, the separation chamber, the dust chamber and the vortex finder. Tangential inlets are preferred for the separation of solid particles from gases (Altmeyer et al., 2003). In this study, the numerical simulation deals with the standard case of reverse flow cyclone with a tangential rectangular inlet. Cyclone dimension used in this simulation is as shown in Table 1.

D

b De

a Sh

H

B ELEVATION PLAN

Fig 1. Tangential cyclone configuration Description of the Pressure Drop models

The pressure drop over the cyclone is an important parameter in the evaluation of cyclone performance. It is a measure of the amount of work that is required to operate the cyclone at given conditions, which is important for operational and economical reasons. The pressure drop is defined as the difference in mean total pressure at the inlet and outlet.. Normally it is the static pressure difference that is measured. This is a reasonable assumption if the area of the inlet and outlet are similar.

The total pressure drop over a cyclone consists of losses at the inlet, outlet and within the cyclone body. The main part of the pressure drop, i.e. about 80%, is considered to be pressure losses inside the cyclone due to the energy dissipation by the viscous stress of the turbulent rotational flow (Ogawa, 1984). The remaining 20% of the total pressure drop are caused by the contraction of the fluid flow at the outlet, expansion at the inlet and by fluid friction on the cyclone wall surface.

In this study, four models have been chosen to predict the pressure drop over a cyclone, namely Shepherd and Lapple (1939), Casal and Martinez (1983), Dirgo (1985), and Coker (1993). In these four models, the total pressure drop in cyclone is either assumed equal to the static pressure drop or as a function of cyclone dimension and pressure drop coefficient.

Shepheard and Lapple model

Shepherd and Lapple (1939) model for static pressure drop over a cyclone is given as

2

2i

gvvHP ρ∆ = (1)

where Hv is the inlet velocity head given as

2e

v DabKH = (2)

Casal and Martinez model

Casal and Martinez (1983) developed a cyclone pressure drop model based on the statistical analysis of experimental data that were collected under isothermal operation for flow in cyclone without particles. Casal and Martinez equation of the pressure drop given as

2

2i

gcvP ρζ∆ = (3)

where ζc is a pressure drop coefficient derived from the statistical analysis on experimental data given as

3333112

.Dab.

ec +⎟⎟

⎠

⎞⎜⎜⎝

⎛=ζ

(4)

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Table 1 Cyclone geometry used in this simulations Geometry a/D b/D De/D S/D h/D H/D B/D Patterson and Munz (1989) 0.5 0.25 0.5 1.06 1.99 3.98 0.25 Parker et al. (1985) cyclone 2 0.38 0.19 0.31 1.13 1.81 4.31 0.38

Dirgo model

Dirgo (1985) also presented a static pressure drop model with consideration of effect of cyclone dimension. The pressure drop in Dirgo is as given in equation (1) and velocity head given as

31

220/

ev )D/B)(D/h)(D/H(

D/SDabH ⎥

⎦

⎤⎢⎣

⎡⎟⎟⎠

⎞⎜⎜⎝

⎛=

(5)

Coker model Coker (1993) model expressed in term of

velocity head based on the cyclone inlet area. Coker gives a pressure drop equation as

vig Hv.P 20030 ρ∆ = (6)

The velocity head in Coker model is as given in equation (2)

RESULT AND DISCUSSION Pressure Drop Prediction under Different Inlet Velocity

Fig. 2 shows that both Shepherd and Lapple, and Dirgo model predict well a cyclone pressure drop of different inlet velocity under room temperature. Static pressure drop model by Shepherd and Lapple, and Dirgo are satisfactory for pressure drop prediction in Patterson and Munz cyclone because the gas inlet and outlet area is nearly equivalent for this cyclone. Static pressure difference within gas inlet and outlet equal to the cyclone pressure drop if inlet and outlet area is similar (Shepherd and Lapple, 1939). Coker’s model yields less accurate fitting to the experimental data (curves are flatter at higher inlet velocity), so as Casal and Martinez’s model.

0

200

400

600

800

1000

0 5 10 15

Inlet gas velocity (m/s)

Pres

sure

Dro

p (P

a) DirgoShepherd & Lapple

Coker

Casal & Martinez

Fig. 2 Evolution of pressure drop with inlet velocity. Comparison between data presented by Patterson and Munz, (1989) and the predictions of the four models (P = 1 bar, T = 293 K, ρ = 3900 kg/m3, D = 0.102 m, Geometry Patterson & Munz (1989)

Pressure Drop Prediction in Different Temperatures

In the various temperatures Coker’s model show a good agreement with an experimental data presented by Parker et al., (1981) as shown in Fig. 3. Casal and Martinez model considerably underestimates the pressure drop prediction while Shepherd and Lapple, and Dirgo model overestimates pressure drop prediction.

Casal and Martinez model prediction on cyclone pressure drop for both various flow rate and temperatures conditions are not satisfactory. This may be attributed by the fact that pressure drop coefficient in this model is derived statistically from experimental data and this model also only validated for an isothermal flow without particle. When the particles are introduced into gas flow, the pressure drop will change due to the influence of the particles. This evidence is caused by particles collision between themselves and the cyclone wall which increases the friction pressure losses (Fredriksson, 1999).

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Pressure drop is a function of the square of inlet velocity, so too high a velocity will cause excessive pressure drop. On the other hand, too low a velocity would cause a low efficiency. A very high inlet velocity would decrease the collection efficiency because of increased turbulence and saltation/re-entrainment of particles. Generally it is found that the optimum operating velocity is around 18 m/s. However the range of practicable cyclone inlet velocity is around 15 – 30 m/s (Shepherd and Lapple, 1939). When cyclones are used as particle separators, the desired to minimize the pressure drop is unfortunately in conflict with the wish to maximize the separation efficiency. Any measure to increase the separation efficiency is normally coupled with considerable increases in pressure drop (Mothes et al., 1981).

0

10

20

30

40

50

60

250 350 450 550 650

Temperature (K)

Pres

sure

Dro

p (P

a) Shepherd & Lapple

Dirgo

Coker

Casal & Martinez

Fig. 3 Pressure drop as a function of operating temperature. Comparison between data presented by Parker et al. (1981) and the predictions of the four models (P = 1.9 bar, ρ = 2300 kg/m3, vi = 1.77 - 2 m/s, D = 0.058 m, Geometry Parker et al. (1981) cyclone 2)

CONCLUSION The model used for the prediction of pressure drop is much depends on the cyclone operating condition. Both Shepherd and Lapple, and Dirgo model is applicable for the pressure drop prediction of various flow rate under room temperature condition. While, for the various temperature condition Coker’s pressure drop model prediction is much better

NOMENCLATURE

a cyclone inlet height (m) b cyclone inlet width (m) D cyclone body diameter (m) De cyclone gas outlet diameter (m) H cyclone height (m) h cyclone cylinder height (m) S cyclone gas outlet duct length (m) B cyclone dust outlet diameter (m) ρg gas density (kg/m3) Hv velocity head (m) vi inlet velocity (m/s) K cyclone configuration and operating

condition constant ζ pressure drop coefficient ∆P cyclone pressure drop (Pa)

REFERENCES Altmeyer, S., V. Mathieu, S. Jullemier, P.

Contal, N. Midoux, S. Rode, J.-P. Leclerc, 2003, “Comparison of different models of cyclone prediction performance for various operating conditions using a general software”, Chem. Eng. and Proc. (Article in press).

Casal, J. and J.M. Martinez-Benet, 1983, “A better way to calculate cyclone pressure drop”, Chem Eng., 99.

Coker, A. K., 1993, Understand Cyclone Design, Chem. Eng. Progress, 51-55. Dirgo, J., and Leith D., 1985, “Cyclone

collection efficiency: Comparison of experimental results with theoretical predictions”, Aerosol Sci. Technolog, 4, 401.

Fredriksson, C., 1999, “Exploratory experimental and theoretical studies of cyclone gasification of wood powder”, Doctoral thesis, Lulea University of Technology, Sweden.

Mothes, H., Sievert, J., and Loffler, F., 1981, “Investigation of the cyclone grade efficiency curves using a light-scattering particle analyzer”, Prociding POWTECH Conf., Birmingham, UK.

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Ogawa, A., 1984, “Separation of particles from air and gasses”, volume 1 and 2, CRC Press, Boca Raton, Florida.

Parker, R., R. Jain, and S. Calvert, 1981, “Particle collection in cyclone at high temperature and high pressure”, Environ. Sci. Technology. 15, 451-458.

Patterson, P.A., and R.J. Munz, 1989, “Cyclone efficiencies at very high temperatures”, Can. J. Chem. Eng. 67, 321-328.

Shepherd, C.B., and C.E. Lapple, 1939, “Air Pollution Control: A Design Approach. In Cyclones”, 2nd Edition, C. David Cooper, and F. C. Alley, pp 127-139, Illinois: Woveland Press Inc.

Silva P. D, Briens C., Bernis A, 2003, “Development of a new rapid method to measure erosion rates in laboratory and pilot plant cyclones”, Powder Technology, 131, 111– 119.