Numerical Analysis for Particle Deposit Formation in Reactor Cyclone

Article pubs.acs.org/IECR

Numerical Analysis for Particle Deposit Formation in Reactor Cyclone of Residue Fluidized Catalytic Cracking Hyungtae Cho,† Bumjoon Cha,† Sungwon Kim,‡ Jaewook Ryu,‡ Junghwan Kim,‡ and Il Moon*,† †

Department of Chemical and Biomolecular Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 120-749, Korea Catalyst and Process R&D Center, SK Innovation, 325 Expo-ro, Yuseong-gu, Daejeon 305-712, Korea

‡

ABSTRACT: Computational particle fluid dynamics (CPFD) simulation was carried out to analyze flow patterns in order to understand the mechanism of deposit formation on the cyclone duct during the residue fluidized catalytic cracking (RFCC) process. The CPFD simulation was based on the multiphase particle-in-cell (MP-PIC) method, in which the particle phase was solved by the stochastic Lagrangian model and the fluid phase was analyzed by the Eulerian method. In the first stage, a lowspeed zone at a duct angle of 90° (an inlet position of 0°) was discovered in the basic design of the cyclone, and this zone was predicted to be the initial region of deposit. Case studies were carried out for several stages of deposit growth to investigate the effects of deposit size on cyclone performance. A scouring phenomenon which hampers deposit growth is expected to occur when the deposit reaches 90 mm in thickness. When the deposit reaches 150 mm, the carryover rate abruptly doubles. particle−fluid interactions.6 Correlations between gas−solid flow in a gas cyclone and the solid loading ratio are described by a numerical model, and the results are validated by the flow features. In this study, the dynamic behavior of the fluid and the particle phase in the cyclone are analyzed. The deposit formation procedure at the cyclone duct is assigned based on fluid velocity and particle distribution. Separation efficiency of the cyclone is investigated as a function of deposit thickness. The results of this study are used to develop a more effective cyclone duct design based on CPFD simulation of particle velocity.

1. INTRODUCTION Residue fluidized catalytic cracking (RFCC) is a typical heavy oil upgrading process. The RFCC process creates additional value by producing highly valuable light hydrocarbons from the atmospheric residue, which contains heavy hydrocarbons. The feed is cracked by catalytic reactions in the riser, followed by the separation of gas products and spent catalysts in a cyclone. A serious problem in this process is the formation of deposit inside the cyclone caused by coke.1 The deposit disturbs multiphase flow in the cyclone as well as a more critical operational problem occuring when the deposit becomes detached from the wall, since these deposits will gradually accumulate at the dipleg and block the pathway of the catalyst going to the regenerator. Cyclic flow of the catalyst in the RFCC process is consequently ceased and additional repair and recovery are needed to ensure proper operation of the process.2 Many studies on deposit formation on the cyclone wall have been conducted, and these have found that the deposit mainly appears at 90−220° from the inlet of the cyclone.3,4 As the quality of crude oil becomes increasingly severe, this deposit problem becomes more and more important. In general, the mechanism of deposit formation that has been reported shows that the wet catalysts by condensed hydrocarbons are attached to the wall according to flow in the lowspeed zone.1,4 A deposit is formed when these viscous catalysts evade the intended route and instead flow to a low speed zone. The velocity of the gas and catalyst particles is a decisive factor in deposit formation. Several researchers5−7 have developed numerical simulation models to understand multiphase flow in cyclones. Kaya and Karagoz7 investigated the isothermal flow characteristics and particle collection efficiencies of conventional and prolonged cyclones. The results, which were computed using the differential Reynolds Stress Model, were verified using experimental values given in the literature. Recently, an approach combining the computational fluid dynamics and discrete element method (CFD-DEM) was developed to explain particle−particle and © 2013 American Chemical Society

2. CPFD GOVERNING EQUATIONS The fluid dynamics are described by averaged Navier−Stokes equations with strong coupling with a discrete particle. The particle momentum equation follows the multiphase particle-incell (MP-PIC) formulation with the addition of a relaxation-tothe-mean term to represent the damping of particle velocity fluctuations due to particle collisions.8−10 The fluid dynamics are described by averaged Navier−Stokes equations with strong coupling with a discrete particle. The particle momentum equation follows the MP-PIC formulation with the addition of a relaxation-to-the-mean term to represent the damping of particle velocity fluctuations due to particle collisions.8−10 The fluid-phase mass and momentum equations are11 ∂θf ρf ∂t

+ ∇·(θf ρf u f ) = 0

(1)

Special Issue: PSE-2012 Received: Revised: Accepted: Published: 7252

September 16, 2012 January 29, 2013 January 31, 2013 January 31, 2013 dx.doi.org/10.1021/ie302509q | Ind. Eng. Chem. Res. 2013, 52, 7252−7258

Industrial & Engineering Chemistry Research ∂(θf ρf u f ) ∂t

Article

+ ∇·(θf ρf u f u f )

= −∇p + F + θf ρf g + ∇·(θf τf )

(2)

where θf is the fluid volume fraction, ρf is fluid density, uf is the fluid velocity vector, p is fluid pressure, τf is the fluid stress tensor, g is the gravitational acceleration, and F is the rate of momentum exchange per volume between the fluid and particles. The constitutive equation for the nonhydro part of the stress, τf, is ⎛ ∂u ⎛ ∂u ⎞ ∂uj ⎞ ⎟ + 2 μδij⎜ k ⎟ τf, ij = −μ⎜⎜ i + ⎟ ∂xi ⎠ 3 ⎝ ∂uk ⎠ ⎝ ∂xj

(3)

where μ is the coefficient of viscosity, which depends only on the thermodynamic state of the fluid. In the CPFD scheme, an ideal gas equation of state is used, where the partial pressure of gas k and total pressure are12,13 pk RT

pk =

p=

MWk

(4)

∑ pk

Figure 1. Cyclone geometry with initial and boundary conditions: (a) initial particle height, (b) inlet boundary, (c) top outlet boundary, and (d) bottom outlet boundary.

(5)

k

Table 1. Material Properties

where R is the gas constant, T is temperature, and MWk is the cular weight of gas species. The equation for particle acceleration is12,13

product gas molecular weight density viscosity inlet velocity

u̅ p − u p 1 1 = Dp(u f − u p) − ∇p + g − ∇τp + dt ρp θpρp τD

du p

67 g/mol 2.85 kg/m3 0.019 cP 16 m/s

(6)

where θp is the particle volume fraction, ρp is particle density, up̅ is the local mass-averaged particle velocity, τp is the particle contact stress tensor, Dp is the drag coefficient, and τd is particle collision damping time.13 The particle volume fraction is associated with the particle distribution function and the particle force per volume in the fluid phase in eq 212 mp θp = f dmp du p dTp ρp (7) ⎛

⎛

⎝

⎝

∭ f ⎜⎜mp⎜⎜Dp(u f − u p) −

78 g/mol 1964 kg/m3 1.25 kg/s

Table 2. Particle Size Distribution

∭

F=−

RFCC catalyst molecular weight density mass flow rate

cumulative weight fraction

size (μm)

0.23 0.35 0.64 0.95 1

30.00 37.50 45.00 52.50 62.50

4. RESULTS AND DISCUSSION 4.1. Flow Pattern of Particles and Fluid in the Reactor Cyclone for the Normal State. Figure 2 shows (a) the particle velocity magnitude and (b) the particle radius of the entire cyclone in the normal state. The particles are rotated four times along the designed helical pathway at the cyclone wall. The particle velocity rapidly decreases at the dust hopper, as shown in Figure 2a. This result is verified by the similarity of the overall flow features between the simulation result and the cold model of the cyclone. The flow features of the particles reach a macroscopically steady state at 3.52 s. As seen in Figure 2b, largesized particles reach the dipleg approximately 2.00 s sooner than small-sized particles. Figure 3 shows the hydrodynamic behavior of the particle and fluid at the cross-section of the duct. Figure 3a shows that initial motion of particles. Evenly dispersed particles are gradually concentrated to the outer wall. At the same time, some the particles intermittently escape from their path and move toward the inner wall. When these irregular particles meet a low-speed zone, the particles are able to adhere to the

⎞ dm p ⎞ ∇p ⎟ ⎟ dm du dT u + p p p p dt ⎟⎠ ρp ⎠⎟ (8)

where mp is the particle mass and Tp is the particle temperature.

3. SIMULATION CONDITIONS Figure 1 shows the geometry of the cyclone with initial and boundary conditions. Initial particle height at the dipleg (a) is 2.18 m and the initial temperature is 520 °C. Inlet pressure and gas velocity at inlet (b) are 2.4 atm and 16 m/s, and the outlet pressures at (c) and (d) are 2.3 and 2.5 atm, respectively. The material properties of the product gas and RFCC catalyst are listed in Table 1. Particle size distribution (PSD) is considered for robust simulation of the particle dynamics in Table 2. All calculations are run to obtain a fully developed three-dimensional mesh. 7253

dx.doi.org/10.1021/ie302509q | Ind. Eng. Chem. Res. 2013, 52, 7252−7258

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Figure 2. Dynamic flow of particles in the cyclone to 10 s: (a) velocity magnitude of the particles [m/s] and (b) radius of the particles [μm].

Figure 3. Flow pattern of the duct at 16.8 s: (a) velocity magnitude of the particles [m/s], (b) velocity magnitude of fluid (m/s), and (c) pressure [Pa].

wall and form the deposit. According to fluid velocity profile, around 90° and from 180° to 270°, the two low-speed zones at the inner wall are identified, and the fluid velocity for the lowspeed zones is lower than 8 m/s (Figure 3b). Among these zones, the ratio of escaped particle is quite higher at near 90° than the area between 180° and 270°. Hence, the deposit is formed initially at 90° in the duct.

Once a deposit forms, the deposit becomes an obstacle for fluid and particle flow. Figure 4 shows that the low-speed zone extends along the fluid flow due to the blocking effect. Consequently, the deposit is also enlarged similarly with the low-speed zone. An industrial report and several researchers are describing this deposit formation area as 90° to 220° on the duct, as shown in Figure 5. 7254



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separation efficiency of the cyclone is changed. Several case studies were investigated to comprehend the effect of various deposit thicknesses on the separation efficiency. As shown in Figure 6, thicknesses of deposits are set with a range from 30 mm to 180 mm, considering deposit samples from a commercial RFCC reactor. For the purposes of simulation, the expected deposit formation region was assumed to be the wall at this geometric position. As the deposit gets bigger, the velocity magnitude behind the deposit decreases, but the pressure increases, as shown in Figures 7 and 8. For cases of deposit thickness of 30 mm and 90 mm, the fluid velocity near the deposit is well preserved as 18 m/s.

Figure 4. Fluid velocity at the duct with deposit thickness of 34 mm [m/s].

Figure 5. Actual shape of the deposit. Figure 7. Velocity magnitude [m/s] of the fluid in the duct at 10 s depending on the maximum thickness: (a) 30 mm, (b) 90 mm, (c) 150 mm, and (d) 180 mm.

Figure 6. Duct geometry depending on the maximum thickness: (a) 30 mm, (b) 90 mm, (c) 150 mm, and (d) 180 mm.

4.2. Flow Pattern of Fluid with Varying Size and Shape of the Expected Deposit on the Duct. As the RFCC process progresses, more particles are attached to the deposit area and the deposit becomes thicker. Thus the deposit thickness depends on the operating period.3 This grown deposit inhibits the pathway of the fluid and the particle, so

Figure 8. Pressure [Pa] of the fluid in the duct at 10 s depending on the maximum thickness: (a) 30 mm, (b) 90 mm, (c) 150 mm, and (d) 180 mm. 7255



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Figure 9. Velocity vector of fluid at 10 s depending on the maximum thickness: (a) 30 mm, (b) 90 mm, (c) 150 mm, and (d) 180 mm.

Figure 10. Flow pattern of particles at the cyclone barrel depending on the maximum thickness: (a) 0 mm, (b) 30 mm, (c) 90 mm, (d) 150 mm, and (e) 180 mm.

However, the fluid velocity is dramatically decreased when the deposit gets thicker. This fluid velocity directly affects the growth rate of the deposit. The higher the fluid velocity, the more deposit is discharged due to the scouring phenomenon or erosion effect by a particle.14 As a result, the growth rate of the deposit is minimized when the duct deposit thickness is approximately 90 mm. The deposit growth rate is fast until deposit thicknesses of 90 mm, and the growth rate is gradually decreased over time. Figure 9 shows vectors of fluid velocity for various deposit sizes; the “a” and “b” sides indicate 270° and 90° in the duct, respectively. The flow field is relatively uniform for thin deposit case (Figure 9a), but the fluid flow is interrupted by the deposit for other cases. Heavy deposit creates a bottleneck at the duct, and the flow is overly concentrated. Because the flow path becomes too narrow, the flow vectors are inclined as shown in the dashed circles of Figure 9b−d. This deviation of the flow field affects the separation efficiency of the cyclone as well as the pathway of particle. 4.3. Particle Flow Pattern and Separation Efficiency. The effect of the deposit size on the flow pattern of the particles was analyzed. Figure 10 shows that the descending angle of the

Figure 11. Weight percentage of catalyst loss.

particles at the barrel increases as the deposit size increases. It can be seen that the particles flow below the white dashed line after turning one round as the deposit varies. The descending angles of (d) and (e) are bigger than the others. Accordingly, the residence time of the particles gets shorter and the 7256



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Notes

separation efficiency decreases. Figure 11 shows the changes in the catalyst carryover rate for different deposit sizes. This result indicates that the separation efficiency of the cyclone is affected by the deposit size inside the cyclone. The carryover rate of the particle is calculated by

The authors declare no competing financial interest.

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ABBREVIATIONS RFCC residue fluidized catalytic cracking CPFD computational particle fluid dynamics MP-PIC multi-phase particle in cell CFD computational fluid dynamics DEM discrete element method PSD particle size distribution

Carryover rate (R c) =

Mass of carryover into the fractionator (Mc) Mass of inflow from the inlet (M i)

(9)

The mass of carryover and inflow was obtained in the result of simulation at the boundary conditions from 5 to 35 s. The carryover rate increases of two and a half times when deposits are thicker than 150 mm, whereas it remains approximately 1.1% in other cases. The deposit with a thickness of less than 90 mm does not have a significant effect on the separation efficiency, which is consistently 98.9%, as shown in Table 3.

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Table 3. Separation Efficiency efficiency

no deposit

30 mm

90 mm

150 mm

180 mm

98.91%

98.90%

98.90%

97.42%

97.32%

However, the carryover rate abruptly increases when the deposit size exceeds a certain thickness, causing abnormal operation of the cyclone. At that time, the mass flow rate of carryover is 117 kg/h, 2.5% of total catalyst flow rate. In terms of the separation efficiency of the cyclone, it seems like an inconsequential matter. Even though the change of carryover is very small compared with the total amount of particle, catalyst loss is more than doubled. Eventually the whole RFCC process could be stopped due to imbalance of the catalyst and feed. According to the flow pattern and efficiency results, the rate of deposit formation is slowed by the scouring phenomenon when the deposit reaches 90 mm in thickness. Therefore, a new and improved design is proposed based on these flow patterns and efficiency results. The new design has a cyclone duct that is the current thickness in an arc of 90 mm within the duct from 90° to 220° such as Figure 6b. With this new design, the turnaround period is expected to be longer due to a decreased rate of deposit formation by the scouring phenomenon.

5. CONCLUSION A CPFD model was developed to analyze the gas−solid multiphase flow in the reactor cyclone of a RFCC. The flow pattern results were validated with data from the cold model of the cyclone. The separation efficiency based on simulation results was approximately 98.9%, which was similar to the actual process data. The location of the deposit formation was predicted for normal operation conditions based on the velocity magnitude at the cross-section of the duct. After deposits formed on the duct at 90°, the deposit extended backward as a result of the blocking effect. Case studies with various deposit sizes were carried out to evaluate the changes in the flow pattern and efficiency of the cyclone. The carryover rate shows a critical point at a deposit thickness of 150 mm, at which point process shutdown occurred. On the basis of these results we propose an advanced design that minimizes the impact of deposit formation.

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AUTHOR INFORMATION

Corresponding Author

*Tel.: +82 2 2123 2761. Fax: +82 2 312 6401. E-mail: ilmoon@ yonsei.ac.kr. 7257



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(20) Lee, Y.; Kim, J.; Kim, J.; Kim, E.; Kim, Y.; Moon, I. Development of a web-based 3D virtual reality program for hydrogen station. Int. J. Hydrogen Energy 2010, 35, 2112−2118. (21) Cho, H.; Cha, B.; Ryu, J.; Kim, S.; Moon, I. CPFD simulation for particle deposit formation in reactor cyclone of RFCC. Presented at the 11th International Symposium on Process Systems Engineering, Singapore, 2012. (22) O’Rourke, P. J.; Zhao, P.; Snider, D. A model for collisional exchange in gas/liquid/solid fluidized beds. Chem. Eng. Sci. 2009, 64, 1784−1797. (23) Kim, S. W.; Lee, J. W.; Kim, C. J.; Koh, J. S.; Kim, G. R.; Choi, S.; Yoo, S. I. Formation and Characterization of Deposits in Cyclone Dipleg of a Commercial Residue Fluid Catalytic Cracking Reactor. Ind. Eng. Chem. Res. 2012, 51, 14279−14288.

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Numerical Analysis for Particle Deposit Formation in Reactor Cyclone

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