Study of gas streaming in a deep fluidized bed containing Geldart's Group A particles

https://doi.org/10.1016/j.ces.2010.02.045Get rights and content

Abstract

The nature of gas streaming in a deep fluidized bed containing Geldart's Group A powder has been investigated in a 30-cm ID cold flow unit. Pressure fluctuations have been measured at 8 locations from 4 to 150 cm above the gas distributor for bed depths and gas velocities ranging from 0.4 to 1.6 m and 0.04 to 0.20 m/s, respectively. In order to study the effect of fines content on gas streaming, two particle size distributions with Sauter mean diameters of 48 and 84 μm were tested for each bed depth and gas velocity. Two distributor plates with differing percentage open area were also tested for their influence on gas streaming. Analysis of pressure fluctuations in the time and frequency domains, in combination with visual observations show that streaming flow emerges gradually at bed depths greater than 1 m. Increased gas velocity and fines content act to delay the onset of streaming, but cannot completely eliminate it over the range of velocities examined. The two different distributor designs had no measurable effect on the streaming flow.

Introduction

Fluidized beds have broad applications in many chemical, pharmaceutical, and mineral processing industries. Numerous studies have been carried out to characterize the hydrodynamics of fluidized beds. Several techniques based on the measurement of the fluctuations of pressure (Johnsson et al., 1995; Svensson et al., 1996; Bai et al., 1997, Bai et al., 1999), voidage (Daw and Halow, 1991; Huilin et al., 1997; Bai et al., 1997, Bai et al., 1999; Ohara et al., 1999) and temperature (Kozma et al., 1996; Woo et al., 2001; Huilin et al., 2002) have been developed and used in the literature. Pressure transducers have been one of the most popular devices due to their simplicity and ease of implementation in industrial facilities. Tamarin (1964) and Hiby (1967) were of the first researchers who attempted to determine the frequency of the pressure fluctuations using visual observations of the pressure signals. Kang et al. (1967) were among the first who used time series analysis techniques such as probability density functions, root mean square of pressure fluctuations, and power spectral density (PSD), to illustrate the time and frequency characteristics of the pressure fluctuations. Lirag and Littman (1971) included autocorrelation and cross-correlation functions to the analysis techniques used by Kang et al. (1967). The autocorrelation function was used to detect signs of periodic phenomena in the pressure fluctuations, while the cross-correlation function was used to calculate the time lag between the pressure fluctuations in the bed and in the plenum. This time lag was used to calculate the propagation velocity of the pressure wave. Fan et al. (1981) and Clark et al. (1991) also discussed similar applications of pressure fluctuations analysis in fluidized bed researches.

Investigating regime transitions in fluidized beds based on analysis of the time series of pressure data has been one of the major concerns of many researchers. Yerushalmi and Cankurt (1979) defined the transition velocity from bubbling to turbulent regime as the point at where the standard deviation of pressure fluctuations reaches a peak. Regime transitions have also been identified by studying the changes occur in frequency distribution of PSD (Lirag and Littman, 1971; Canada et al., 1978; Satija and Fan, 1985; Johnsson et al., 1995; Svensson et al., 1996).

The study of pressure fluctuations has been widely continued until recent days. One of the important operating parameters that can greatly affect the fluidized bed hydrodynamics, and thus the in-bed pressure fluctuations, is the bed depth. Grace and Sun (1991) studied the effect of bed depths varied from 40 to 100 cm on the differential pressure fluctuations in a bed of FCC particles. They found that the transition velocity from bubbling to turbulent regime is almost independent of the bed depth. Similar results were reported by Satija and Fan (1985) and Jin et al. (1986). Falkowski and Brown (2004) studied the pressure fluctuations for a range of variables including bed depth in a fluidized bed of Geldart B and D particles to determine the effect of these parameters on the PSD graph. They reported that dominant frequency decreases with increasing the bed depth from 8.6 to 50.8 cm.

The bed depth, which is directly related to the material inventory of the fluidized bed, is indeed one of the important operating parameters in various applications of fluidized beds. Achieving specific efficiencies or throughput can lead to the necessity of employing deep fluidized beds. In these cases, maintaining specified gas residence times, low particle entrainment, and a good fluidization quality possess special importance. Recent studies have shown that, in a sufficiently deep bed of Geldart's group A particles (Geldart, 1973) gas bypassing may occur when the flow rate of the fluidizing gas is increased beyond the minimum fluidization velocity (Wells, 2001; Karri et al., 2004; Issangya et al., 2007). When this phenomenon occurs, the fluidizing gas bypasses the bed in the form of streams of gas, leaving a large fraction of the bed unfluidized or poorly fluidized. Since many industrial fluidized bed processes might work with deep beds, gas streaming is a potential problem that can decrease the efficiency of these chemical and physical fluidized bed processes.

With the exception of the previously cited works (Wells, 2001; Karri et al., 2004; Issangya et al., 2007), there is little discussion of streaming flow in the open literature. This may be attributed to the fact that laboratory scale fluidized beds are typically not operated with sufficient bed depth for streams to appear (Karri et al., 2004). Some previous researchers have reported the presence of non-uniformity in the radial gas distribution (Rowe et al., 1978; Farag et al., 1997). However, they have not considered it as an important phenomenon to be separately studied. For instance, Farag et al. (1997) conducted experiments in 0.3 and 0.5 m diameter columns with a 160 cm deep bed of FCC particles and observed an axi-symmetric bubble flow “in spite of the careful design of the grid and frequent checks of column verticality”. They attributed this to the influence of the return of particles from the cyclone dipleg. They noticed that increasing the bed temperature enhanced the uniformity of the radial bubbling activity.

The concept of gas streaming was first reported in the literature by Wells (2001). He performed experiments in large scale units with up to 2.5 m diameter and 5 m bed depth and observed streaming flow under conditions that were expected to lead to operation in the bubbling regime. He studied the effects of fines content (particles smaller than 44 μm), distributor design, anti-static agents, baffles, and bed depth. Presumably due to restrictions surrounding the publication of industrial data, details of his findings were limited; however he reported no influence of the various parameters, with the exception of bed depth and baffles. The streaming phenomenon was attributed to gas compression caused by the pressure head of the deep bed over the distributor. The onset of streaming corresponded to an increase in the emulsion suspension density above that at minimum fluidization. The bed then defluidized and gas streaming occurred. Wells (2001) concluded that when the ratio of the density at minimum fluidization to the density of the emulsion phase becomes less than some critical value for a given bed depth, streaming occurs. However, his criterion was not a direct function of the operating condition such as bed depth and gas velocity. Instead, the emulsion phase density was a function of voidage at minimum bubbling and pressure at the surface of fluidized bed.

Karri et al. (2004) investigated the formation of streaming flow in a column of 0.3 m inner diameter and 4.9 m height, and tried to characterize different aspects of this phenomenon. They used FCC particles with average diameter of 70 μm and a static bed depth of 2 m. They found that the standard deviation of pressure drop in a bed exhibiting streaming was much greater than a uniformly fluidized bed. They also reported that for all combinations of operating conditions investigated, the addition of a sufficient amount of fines to the bed of Geldart's Group A particles was able to delay the streaming. This was contrary to the findings of Wells (2001). Karri et al. (2004) also evaluated the use of baffles and found that two baffles separated vertically by a distance of 0.76 cm eliminated the streaming flow. The value of 0.76 cm was chosen because it corresponded to the maximum bed depth beyond which streaming occurred in a non-baffled bed.

Issangya et al. (2007) performed another study in a 0.9-m-diameter and 6.1 m tall test unit. FCC catalyst with fines contents of 3% and 12% and median particle diameters of 80 and 74 μm, respectively was used as the bed test material. Results for gas velocities up to approximately 1 m/s were reported. Four pressure transducers were mounted at four radial positions across axial heights spanning 61 cm to detect the presence of streaming flow. They attributed the larger differential pressure fluctuations measured by certain transducers to the passage of streams closer to that transducer. Issangya et al. (2007) also concluded that the maximum in the plot of standard deviation of the pressure fluctuation measured across the entire bed versus gas velocity, which has been shown in the literature to be an indication of the transition between the bubbling and the turbulent fluidization regimes, is not present for deep beds that are subject to streaming. The absence of the maximum in the graph of standard deviation of pressure fluctuation versus gas velocity which is reported as an indication of streaming in deep beds by Issangya et al. (2007) is contrary to the findings of Ellis (2003). Ellis (2003) who performed a comprehensive study on the bubbling-turbulent transition velocity for bed depths as high as 1.5 m, reported that although by increasing the bed depths the maximum shifts to the higher gas velocities, it is always present in the graph.

Streaming flow in deep beds is a relatively new phenomenon reported in the literature in fluidized beds and there is still a great deal of uncertainty and contradiction between results of different investigations. For instance, while Wells (2001) found no effect of fines content, others (Karri et al., 2004; Issangya et al., 2007) reported an influence of fines on the streaming flow. The mathematical work performed by Wells (2001) to predict the onset of streaming flow was not a direct function of the operating conditions such as bed depth and gas velocity and seems not to be able to predict the correct situation for various cases. He also has not presented a comparative analysis between different bed depths to clarify the presence of streaming flow.

These facts indicate that further experimental and theoretical work is still required to shed light on this phenomenon. The objective of the present work is to verify the presence of the streaming flow, to find the differences between the hydrodynamics of fluidized beds with different bed depths, and to investigate the possible reasons for these differences and their relationship to the presence of streams. For this purpose, pressure fluctuations have been used to perform a comparative analysis of the influence of different parameters on the fluidized bed behavior. The pressure fluctuations have been measured at several locations along the fluidized bed for various combinations of bed depth, gas velocity, particle size and distributor design in a 0.3 m diameter column. Quantitative analysis methods in both the time and frequency domains have been used to extract and evaluate useful information regarding to the fluidized bed behavior under these different conditions.

Section snippets

Fluidized bed

The fluidized bed unit was made of a cylindrical Plexiglas column with an inner diameter of 30 cm and height of 3.3 m (Fig. 1). The column was equipped with an internal cyclone and a dipleg to continuously return entrained particles to the bed during operation. The distance between the dipleg exit and the distributor was 0.19 m for all bed depths. The cyclone gas exit was connected with a flexible hose to a barrel with filter cloth stretched over openings on the top to prevent very fine particles

Analysis methods

Time series of pressure fluctuations collected with the differential pressure transducers have been analyzed in the time and frequency domains. Key properties that are extracted from the time series through these analyses are briefly explained in the following sections.

Visual observations

The use of a transparent Plexiglas vessel in the present study permitted us to make visual observations during experiments. This section is based on the observations made for the coarse FCC particles (3% fines content); however, it covers low and high gas velocities and both the HPD and LPD gas distributors. The observations showed that in the case of the 40 cm bed depth, bubbles were formed over the entire bed cross section and the entire bed appeared to be fluidized. For the 80 cm bed depth,

Conclusions

A series of experiments was conducted to study the effect of bed depth, superficial gas velocity, fines content, and distributor pressure drop on streaming flow in a 0.3-m diameter fluidized bed. The analysis of the pressure fluctuations time series for bed depths ranging from 40 to 160 cm revealed that the normal bubbling fluidization is gradually compromised by increasing the bed depth. This conclusion is based on the gradual increase of the autocorrelation function, the decrease in the rate

Nomenclature

ACFautocorrelation function
ffrequency, Hz
Hbed depth, m
icounter
kcounter
ntime series length
Rxycross correlation function
ttime, s
Ttime series period, 1/s
U0superficial gas velocity, m/s
xiith component of the x time series
x¯average of the x time series
ytime series

Greek letters

γxycoherency between x and y time series
τdelay time
Φxxpower spectral density for x time series
Φxycross power spectral density between x and y time series
Φyypower spectral density for y time series

References (39)

  • J. van der Schaaf et al.

    Non-intrusive determination of bubble and slug length scales in fluidized beds by decomposition of the power spectral density of pressure time series

    International Journal of Multiphase Flow

    (2002)
  • J. Yerushalmi et al.

    Further studies of the regimes of fluidization

    Powder Technology

    (1979)
  • D. Bai et al.

    Chaotic behavior of fluidized beds based on pressure and voidage fluctuations

    A.I.Ch.E. Journal

    (1997)
  • D. Bai et al.

    Characteristics of gas-fluidized beds in different flow regimes

    Industrial and Engineering Chemistry Research

    (1999)
  • G.S. Canada et al.

    Flow regimes and void fraction distribution in gas fluidization of large particles in beds without tube banks

    A.I.Ch.E. Symposium Series

    (1978)
  • Daw, C.S., Halow, J.S., 1991. Characterization of voidage and pressure signals from fluidized beds using deterministic...
  • Ellis, N., 2003. Hydrodynamics of gas–solid turbulent fluidized beds. Ph.D. Dissertation, University of British...
  • D. Falkowski et al.

    Analysis of pressure fluctuations in fluidized beds

    Industrial Engineering Chemistry Research

    (2004)
  • L.T. Fan et al.

    Pressure fluctuations in a fluidized bed

    A.I.Ch.E. Journal

    (1981)
  • Cited by (13)

    • Experimental study and CPFD simulation on circumferential flow heterogeneity in a disc-donut catalyst stripper

      2020, Chemical Engineering Journal
      Citation Excerpt :

      Fig. 17 shows the slice-view of the simulated instantaneous solids holdups at different simulation times. The existence of unfluidized zones on baffles and the gas cushion blow baffles as reported in literature [9,35,36] was captured successfully. The formation and development of the gas bypassing in the disc-donut stripper can also be observed.

    • Experimental study of non-uniform bubble growth in deep fluidized beds

      2018, Chemical Engineering Science
      Citation Excerpt :

      Pressure transducer (Fan et al., 1981; Zhao and Yang, 2003; Bi, 2007) is another popular device in industrial facilities due to its simplicity. Gas streaming flow for FCC particles in a deep fluidized bed was investigated by placing differential pressure transmitters in four quadrants across a section of the fluidized bed (Issangya et al., 2007) and analysis of the pressure fluctuations in time and frequency domains (Karimipour and Pugsley, 2010). The combination between pressure fluctuations analysis and CFD also provides a deep understanding of fluidization quality (Lungu et al., 2016; Ramirez et al., 2017).

    • Experimental study and discrete element method simulation of Geldart Group A particles in a small-scale fluidized bed

      2017, Advanced Powder Technology
      Citation Excerpt :

      Typical FCC particles have a bulk density of 0.8 to 0.96 g/cm3 and a particle size distribution ranging from 10 to 150 µm and average particle size of 60 to 100 µm. Extensive experimental work has been reported on the fluidization behavior of group A particles, especially for FCC particles [2–5]. With the continuous evolvement of computer hardware and development of theory and numerical algorithm, computational fluid dynamics (CFD) has been demonstrated a complementary tool to experiment to investigate gas–solid flow in multiphase systems [6].

    • Instability of uniform fluidization

      2017, Chemical Engineering Science
      Citation Excerpt :

      In the case of a given distributor, deep solids beds should be introduced more gas stream to attain uniformity. Karimipour and Pugsley (2010a, 2010b) reported that with the onset of gas stream at bed depths greater than 1 m (total solids pressure loading ΦT = 12), and quality of fluidization dramatically drops in deeper beds (ΦT = 16) and in shallow beds (ΦT = 8) smooth fluidization with uniform bubble activity is obtained. Similar results can be obtained by other studies as well (Cocco et al., 2001;Wells, 2001; Karimipour and Pugsley (2010a, 2010b).

    View all citing articles on Scopus
    View full text