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Hydrodynamics of Bubble Column Reactors at High Gas Velocity: Experiments and Computational Fluid Dynamics (CFD) Simulations Mohan R. Rampure,†,‡ Amol A. Kulkarni,† and Vivek V. Ranade*,† Industrial Flow Modeling Group, National Chemical Laboratory, Pune-411 008, India, and Department of Chemical Engineering, Indian Institute of Technology-Bombay, Powai, Mumbai-400076, India
This paper focuses on the modeling of flow and mixing in a bubble column reactor operated at high gas velocities (up to 0.40 m/s). A dual-tip conductivity probe was used to measure local void properties such as local time-averaged gas holdup, chord length distribution, bubble velocity distribution, and interfacial area. Chord length distribution was converted to bubble size distribution, using the backward transformation method. Liquid-phase mixing time measurements were conducted using a conductivity probe. A computational fluid dynamics (CFD) model was developed to simulate the unsteady gas-liquid flow in a bubble column using commercial code FLUENT 6.2. The time-averaged flow properties predicted by CFD simulations were compared with the experimental data. The role of unsteady flow structures in mixing was studied. The “multiple snapshots” approach was used to simulate the mixing time using CFD. The mixing times that were predicted for all superficial gas velocities compared favorably to the measured values. This study of the hydrodynamic behavior of a bubble column at higher gas velocity provides a basis for understanding and simulating solid suspension (or solid mixing) in slurry bubble column reactors. 1. Introduction Bubble column reactors are simple in construction and operation. They are widely used in many industrial processes (e.g., gas-to-liquid (GTL) conversion, wastewater treatment, and catalytic hydrogenation of olefins).2 In bubble column reactors, the reactant gas itself provides the stirring action that is required to conduct gas-liquid and gas-liquid-solid interactions and reactions. There are many industrial applications where a large volume fraction of solid catalyst is used. For example, in slurry bubble column reactors that are used for Fischer-Tropsch synthesis, the solid catalyst volume fraction is 20%-40%. In such a case, the effective utilization of the catalyst is essentially dependent on the heat- and mass-transport rates and uniform suspension of catalyst particles within the reactor.3-6 The uniformity of solid or solids mixing is largely dependent on the superficial gas velocity, properties of the liquid phase, and the particle sizes.7 Typically, in regard to the use of lower superficial gas velocities (although it is higher than the incipient suspension velocity), the solid concentration along the height of column decreases away from the sparger. Such situations affect the performance of the reactor and the catalyst remains underutilized. This dictates that the reactor must be operated at sufficiently high superficial gas velocities (above the critical suspension velocity) and an understanding of the relevant hydrodynamic features is required. Although the construction and operation of bubble column reactors is rather simple, the hydrodynamics is not. In the buoyancy-driven flows as in a bubble column reactor, the bubbles primarily supply energy, which drives the flow and mixing. The flows are inherently unsteady and the dynamic characteristics of such flow are dependent on the superficial gas velocity. Although the experimental and modeling studies of bubble column reactors operated with low gas velocity ( 0.20 m/s. Nottenkamper et al.23 measured the local gas holdup using an optic probe for UG e 0.342 m/s, whereas, in some analyses,
the “dynamic gas disengagement” method was also used to measure the bubble classes.24,25 Given the paucity of the information about hydrodynamics in a bubble column at high gas velocity, here, we have experimentally measured the average and local hydrodynamic parameters (using conductivity probes) and used the measured data to evaluate CFD simulations. The experimental setup and the experiments are discussed in the following section. The CFD model and selection of simulation parameters are discussed in section 3, followed by a discussion of the results and conclusions. 2. Experimental Section 2.1. Experimental Setup. Experiments were performed in an acrylic cylindrical column (0.2 m in diameter and 2 m in height), with air and tap water representing a gas-liquid system. A sieve plate sparger with 314 holes 1.2 mm in diameter arranged in a square pitch of 5 mm covering the entire cross section of the column was used in all the experiments. Provision was made on the column wall for mounting the dual-tip conductivity probe at two different positions away from the sparger (H ) 0.155 m and H ) 0.65 m). Figure 1 shows a schematic of the experimental setup. The measurements of the local-phase conductivity were conducted at superficial gas velocities in the range of 0.01-0.40 m/s. The gas flow rates were measured and controlled using a set of precalibrated rotameters and needle valves. In all the experiments for various superficial gas velocities, a dispersed liquid height of 1 m was maintained (HD/D ≈ 5, where HD is the height of the dispersed phase).
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Figure 2. Measurement techniques for gas-phase properties and mixing time: (a) dual-tip conductivity probe, (b) calibration for PDT using gas holdup, and (c) raw conductivity signal acquired after impulse addition of NaCl solution in the column.
2.2. Measurement of Gas-Phase Flow Characteristics Using a Conductivity Probe. The technique of using an electrical resistivity probe (conductivity probe) to determine the bubble size and bubble velocity in gas-liquid flows was proposed by Neal and Bankhoff.26 The measurement principle and different signal analysis methods for the case of a dual-tip probe can be found in previous literature.22,27,28 The dual-tip conductivity probe used in this work was fabricated in-house from a pair of stainless steel needles (177.8 µm in diameter and 20 mm long). The needles were placed horizontally, one above the other, with a fixed distance between the two (1.34 mm). A schematic of the designed probe is shown in Figure 2a. The data were acquired using a microcomputer, via a 16bit PCMCIA A/D converter card. The data was acquired at a sampling frequency of 5000 Hz for 200 s. The acquired conductivity-time data were subjected to noise removal and phase discrimination, using an in-house code. Details of the functioning of a conductivity probe for phase (gas and liquid) identification can be found in the work of Buwa and Ranade.29 The phase discrimination threshold was set from the comparison of the signal achieved using a probe and the captured images of bubbles using a high-speed camera in a model rectangular bubble column (20 cm × 5 cm × 120 cm). Figure 2b shows that a threshold of 10% of the maximum peak is nearer to the photographically measured gas holdup. There-
fore, a phase discrimination threshold of 10% of the maximum peak was used for further analysis. The signal was acquired at two vertically positioned tips: an upstream tip (tip-1) and a downstream tip (tip-2). The time-averaged gas holdup was estimated from the ratio of dwell time and the total data acquisition time. Bubble velocity was obtained from the distance between the two tips and the net time lag for bubble-tip interaction for two tips.22,30 The chord lengths were measured at both tips, using the dwell time and the bubble velocity for individual bubbles. After setting the threshold and discriminating the phases, the next step was to identify the signals delivered by the probe when a bubble is pierced by the front and rear sensors. The two signals obtained were not perfectly identical; a set of filtering criteria proposed by Dias et al.21 was used to distinguish between the pair of signals resulting from identical bubbles. In the analysis, it was assumed that the upward and downward movements of the bubbles were in the vertical direction. The unwanted sections of the signals that do not belong to the same bubble were removed from further data analysis procedures. The pair of signal sections where a bubble hits the tip-2 probe first was also neglected. The selection of suitable signal pairs was based on the following conditions:
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trise1,i < trise2,i and tfall1,i < trise2,i
(1a)
trise1,i > trise2,i and trise1,i > tfall2,i
(1b)
Hence, all pairs that did not satisfy the conditions given in eqs 1 were considered for further analysis. The paired events were further verified by estimating the bubble passage velocity (l/ ∆ti) from the distance between the probe tips and the dwell time at an individual probe. If (l/∆ti) > 0.2 m/s, the signals were considered to yield the bubble velocity. Based on the dwell time at the probes, the data were verified against the criteria proposed by Yasunishi et al.:30
0.75
0.05 m/s),
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Figure 6. Chord length/bubble size distribution and bubble velocity distribution: (a) Ug ) 0.05 m/s, H ) 0.155 m, (b) Ug ) 0.4 m/s, H ) 0.155 m, (c) Ug ) 0.05 m/s, H ) 0.65 m, (d) Ug ) 0.4 m/s, H ) 0.65 m, (e) H) 0.155 m and (f) H) 0.65 m.
the average bubble size variations obtained at different measurement positions are shown in Figure 7b-d and were observed to be reasonably uniform throughout the column. 4.2.2. Overall Gas Holdup. A preliminary step to validate the CFD model was to compare the overall gas holdup in the column. The overall gas holdup in the cylindrical bubble column was measured visually for gas velocities in the range of 0.010.4 m/s (the height-to-diameter ratio was fixed at H/D ) 5). Tang and Heindel46 reported the time dependency of gas holdup for the system of air and tap water. Therefore, fresh tap water was used in all the experiments and the volume fraction was measured immediately (within 1 h). The measured values of the overall gas holdup are shown in Figure 8. Recently, Chaumat et al.47 reported the gas hold-up data in a column with a diameter of 0.2 m for a sparger with two hole diameters (0.0005 and 0.001 m). Their results with a sparger that had holes 0.001 m in diameter were quite similar to the present results obtained with a sparger that had holes 0.0012 m in diameter. The time-
averaged local phase properties were also compared with the experimental data, as discussed in the next section. 4.2.3. Local Gas Hold-Up Profiles. Figure 9 shows the radial profiles for time-averaged local gas holdup for four different gas velocities and at two different axial locations. The local gas holdup measured by the dual-tip conductivity probe was compared with the values obtained using the inclined (40°) single-tip conductivity probe.44 The results for the radial profile of gas holdup using an inclined single-tip conductivity probe are shown in Figures 9a-9d. The radial plot for time-averaged gas holdup measured using the dual-tip conductivity probe predicted lower values, in comparison to the inclined probe (single tip, 40°). The reason for this difference in values was due to the probe configuration. Because of the fact that, in the dual-tip probe, needles were placed horizontally (with two tips aligned in vertical direction), the possibility of the bubble diversion or breaking of the bubbles at the needle surface was greater than the possibility of bubbles piercing the needle tips.48
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Figure 7. Radial profile of the number-weighted-average bubble size: (a) Ug ) 0.05 m/s, (b) Ug ) 0.10 m/s, (c) Ug ) 0.20 m/s, and (d) Ug ) 0.40 m/s.
Figure 8. Effect of superficial gas velocity on overall gas holdup.
Hence, when compared with the inclined single-tip probe, the local gas hold-up measurements using the horizontal probe showed comparatively lower values (∼25%). The results predicted by the CFD model show good agreement with the experimental data. The experimental values of Chaumat et al.47 for local gas holdup measured using a double-optic probe were also shown in Figures 9a and 9b. 4.2.4. Axial Velocity Profiles. The profiles of time-averaged axial liquid velocity obtained from the CFD simulations are shown in Figures 10a-10d. The CFD simulations showed good comparison with the experimental data of Sanyal et al.12 (using the CARPT technique) at a superficial gas velocity of 0.10 m/s (see Figure 10b). For a gas velocity of 0.40 m/s, not much difference in the time-averaged axial velocity profile values was observed for measurements that were conducted at two axial locations (see Figure 10d). The measured and simulated radial profiles of the timeaveraged axial gas velocity are shown in Figures 11a-11d. CFD simulations showed good agreement with the mean bubble
velocity measured using the dual-tip conductivity probe (see Figure 11a-c). The comparison for higher superficial gas velocity however showed a noticeable discrepancy (see Figure 11d). One of the reasons for this discrepancy may be the increased possibility of bubbles not cutting both the probe tips at higher gas velocity. This poses a difficulty in finding the pair of signals that result from an identical bubble. 4.2.5. Interfacial Area. Interfacial area is an important parameter in determining the mass-transfer coefficient. The local interfacial area was determined from the average bubble size and the local time-averaged gas holdup measured at nine points along the column diameter (at a spacing of 2 cm) and at two different axial locations (see Figure 12). These radial profiles show that higher interfacial area values occur at the center of the column, compared to the near-wall region. The effect of superficial gas velocity on the interfacial area is shown in Figure 12c. The interfacial area recorded near the sparger (H ) 0.155 m) showed a decrease at a gas velocity of 0.10 m/s. This is caused by large bubbles formed in the transition flow regime at the near-sparger region. When the variation of the average interfacial area (a (1/m)) is analyzed with the superficial gas velocity, we observed a power-law relation a ∝ Ug0.4, which is consistent with the observations reported in the literature.53,54 The values of the proportionality constant at two axial locations (0.155 and 0.65 m) were determined to be 127.69 and 114.92, respectively (see Figure 12c). 4.3. Liquid-Phase Mixing. Ranade et al.49 discussed mixing time definitions in various forms. “Mixing time” can be defined as the time measured from the instant of tracer addition until the reactor content has reached a specified degree of homogeneity. Different ways of identifying this degree of homogeneity were used in this work. The most common method is adding the tracer at the liquid surface and detecting the tracer
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Figure 9. Radial profile of the time-averaged gas holdup: (a) Ug ) 0.05 m/s, (b) Ug ) 0.10 m/s, (c) Ug ) 0.20 m/s, and (d) Ug ) 0.40 m/s.
Figure 10. Simulated profiles of time averaged axial liquid velocity: (a) Ug ) 0.05 m/s, (b) Ug ) 0.10 m/s, (c) Ug ) 0.20 m/s, and (d) Ug ) 0.40 m/s.
concentration at the various locations in the reactor vessel. In this paper, the tracer mass-fraction history was recorded at three different locations (H ) 0.155, 0.5, and 0.845 m). These three
locations correspond to the same locations used for the experimental measurements using a conductivity probe. Mixing time was recorded as the time at which 75% of homogeneity
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Figure 11. Radial profile of the time-averaged axial gas velocity, compared with the measured number-averaged bubble velocity: (a) Ug ) 0.05 m/s, (b) Ug ) 0.10 m/s, (c) Ug ) 0.20 m/s, and (d) Ug ) 0.40 m/s.
Figure 12. Gas phase interfacial area: (a) H ) 0.155 m and (b) H ) 0.65 m. (c) Effect of gas velocity on interfacial area .
of the tracer mass fraction is achieved in every cell of the computational domain (see Figure 13a). The degree of uniformity can be specified based on the concentration variation from maximum tracer concentration or from the minimum tracer concentration in the reactor vessel (see Figure 13b). To eliminate the possible influence of the detector location, the degree of uniformity was based on the
percentage of the vessel volume containing a specified amount of tracer concentration. The profile for the percentage of the reactor volume that contains (1 ( 0.01P) C∞ is shown in Figure 13b, where the value of P is 5%, 10%, and 25%. The mixing time was predicted using P ) 25% for both CFD simulations and the experimental measurements. To calculate the mixing time, initially (at t ) 0), the tracer/species mass fraction was
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Figure 13. Mixing time based on CFD simulation: (a) tracer history recorded at different locations and (b) fraction of reactor volume containing maximum/ minimum tracer concentration in reactor and also within (1 ( P)C∞.
set to 1 in the region, comprising 0.1% of the reactor volume at the location of tracer introduction. The tracer mass fraction in the remaining column was set to zero. The transient simulations of flow and tracer mass fraction were then performed. Note that it is very important to achieve very stringent convergence of all the balance equations, especially of the overall mass balance equation (continuity equation) to ensure that the total amount of tracer present in the column remains the same with time. If there is even a small error in the continuity equation, it usually leads to a loss or gain of total tracer present in the column, leading to severe difficulties in estimating the mixing time. Therefore, it is essential to use very small time steps and a large number of internal iterations per time step to control possible accumulation errors over the overall mixingtime prediction. To reduce the burden on computational resources, it is worthwhile to explore a “multiple snapshot” approach, as proposed by Buwa and Ranade.19 In this approach, after the transient gas liquid flow in the bubble column has attained a quasi-steady state, flow fields after specific time intervals (snapshots) are stored. Before such snapshots are stored, care is taken to ensure that the continuity (mass balance) for the each computational cell satisfies the stringent criterion (by performing simulations with lower values of momentum underrelaxation parameters and a very large number of internal iterations). Such stored snapshots of flow field are then used to solve only the tracer mass-fraction equation for the interval between the snapshots. At the beginning of the new interval, the tracer concentration distribution within the column is stored
and then used for further solution using the next snapshot of flow field. Such an approach was used in this work. Based on our earlier work on estimating time scales of gas-liquid flow in bubble columns (Rampure et al.13), the guidelines discussed by Buwa and Ranade19 were used to identify a reasonable interval between successive snapshots to be 2 s. A preliminary study was conducted using a velocity flow field at every time interval of 0.5 s and compared with the 2 s interval snapshots. Mixing times for all gas flow rates predicted by solving flow as well as species/tracer simultaneously were also compared with the mixing time values predicted using the “multiple snapshot approach”. The mixing time, using a snapshot interval of 0.5 and 2 s, showed a difference of
