Visualization of particle aggregation and effects of particle properties on cluster characteristics in a CFB riser

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Chemical Engineering Journal 168 (2011) 376–389

Contents lists available at ScienceDirect

Chemical Engineering Journal

journa l homepage: www.e lsev ier .com/ locate /ce j

isualization of particle aggregation and effects of particle properties on clusterharacteristics in a CFB riser

ing Xu, J.-X. Zhu ∗

article Technology Research Centre, Department of Chemical & Biochemical Engineering, The University of Western Ontario,151 Richmond Street, London, Ontario, Canada N6A 5B9

r t i c l e i n f o

rticle history:eceived 3 August 2010eceived in revised form 10 January 2011ccepted 11 January 2011

a b s t r a c t

The particle aggregation was studied in a circulating fluidized bed riser. The flow structure and theformation of clusters were visualized by a high-speed digital image system. The particle aggregation ischaracterized by analyzing the images frame by frame, as well as the instantaneous solids concentration

eywords:ydrodynamicsarticle propertiesggregationicroflow structure

data obtained by the optical fiber probe. The results indicated the smaller and the lighter particles havehigher potential to aggregate than the larger and heavier particles. The effects of particle sphericity werenot as significant as the effects of particle density and size. A new cluster characteristic, cluster numberfraction, was defined in this study. Other aggregate properties, including cluster time fraction, clustermean existence time and cluster frequency were also compared with the analyses of solids concentration.The study elucidated the effects of particle density, size and sphericity on particle aggregation properties.

luster

. Introduction

Circulating fluidization technology has found its various appli-ations in the field of chemical, petrochemical, environmental andnergy industries. Due to its importance, a significant number ofcientific studies focusing on the characteristic of gas–solid twohase flow in the circulating fluidized bed have been conducted.he numerous studies have shown that the operating conditions1–4], the riser geometry and structure [5–10], the solids inven-ory [11] as well as the particle properties [12–14] are some ofhe main factors influencing the axial and radial distribution ofolids concentration and particle velocity. Under a certain range ofperating condition [15], a core–annulus structure can be observedith a rapid upward flowing dilute core region in the riser cen-

er surrounded by a relatively dense annulus in the wall region,here solids may move downwards or travel upwards at a much

lower velocity [12,16–18]. This flow pattern often characterizeshe macroscopic flow structure of gas–solid suspension in CFB ris-rs.

However, the analysis of the microstructure of the gas–solid two
hases is considered complex and remains vague. The microflowtructure is usually identified as the behavior of the particle aggre-ates or clusters, which are defined as dense clouds of particlesaving significantly more particles per unit volume than the sur-
∗ Corresponding author. Tel.: +1 519 661 3807; fax: +1 519 850 2441.E-mail address: [email protected] (J.-X. Zhu).

385-8947/$ – see front matter © 2011 Elsevier B.V. All rights reserved.oi:10.1016/j.cej.2011.01.044

© 2011 Elsevier B.V. All rights reserved.

rounding dilute regions [19]. The concept of particle clustering firstappeared in the early years of fast fluidization study [20]. The in-depth work on particle aggregation, initiated by Yerushalmi et al.[21], and followed by many later work, have indicated that inthe regime with core–annulus flow structure, the particles in CFBtend to aggregate and form clusters, which flow quite differentlyfrom the single particle [15,21–23]. Therefore, the gas–solid flowin CFBs is often characterized by the existence of particle aggre-gates or clusters [19,24]. Some experimental studies on clusterproperties have been conducted by using different measurementtechniques in recent years. Chan et al. used positron emission parti-cle tracking to study the particle velocity and overall solids mixingin a CFB. They found that the cluster formation is closely linkedwith the core–annulus flow structure, which often appears undera restricted range of Ug and Gs [15]. Bi et al. [19] studied the evo-lution and transformation of various types of “clusters” throughobservation made in a two-dimensional circulating fluidized bed.The images of particle aggregations were analyzed and four formsof cluster were classified and described. Soong et al. [25] employedthe dual capacitance probes to obtain cluster sizes and velocityby analyzing the simultaneous solids concentration at two closevertical locations. Manyele et al. [23] reported their investigationof the aggregate properties in a high-flux and high-density riser,
based on the solids concentration measurements by using a fiberoptic probe. The aggregate frequency, time fraction, existence time,average solids concentration and cluster vertical dimension wereestablished using sensitivity analysis. Lackermeier et al. studied theparticle aggregates properties by applying high-speed video tech-
dx.doi.org/10.1016/j.cej.2011.01.044

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dx.doi.org/10.1016/j.cej.2011.01.044

J. Xu, J.-X. Zhu / Chemical Engineering Journal 168 (2011) 376–389 377

Nomenclature

D riser diameter (m)dp Sauter mean diameter of particle (m)dvl cluster vertical length (m)Fc cluster time fractionfc cluster frequency (Hz)Flc cluster number fractionGs solids circulation rate (kg/m2 s)H riser height (m)Ns number of consecutive samples above the critical

solids concentrationTc minimum time interval for cluster (s)Ug superficial gas velocity (m/s)Vc cluster vertical velocity (m/s)Vp particle velocity (m/s)Y half of riser width (m)y lateral coordinatesZ height from riser bottom (m)�p density of particle (kg/m3)

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ique in combination with the laser sheet technique. They proposedmethod to pre-process digital images and made the calculationf aggregates shapes and velocities possible. Shi et al. [26] con-ucted the experimental study on the visualization of aggregateroperties by particle imaging velocimetry. They determined theoundary of clusters and the influence of the clusters on the floweld, as well as the categories to classify particle aggregations. Theain parameters of the recent studies relative to the particle aggre-

ation are listed in Table 1, according to the format Harris et al. [27]ummarized.

To summarize the previous studies, it has been found that mostf the researchers analyzed the particle aggregates by applyinghe non-intrusive methods of visualization [19,31–33], or usingntrusive probes [23,25], but few studies have been carried outy combining these two complementary methods together [34].he intrusive probes are capable of acquiring the instantaneousolids concentration and identifying the clusters. However, it isore effective for describing local flow behaviors other than map-

ing the overall flow structure. On the other hand, the visualizationechnique is practical to obtain the whole image of flow, but it is

ore successful under dilute solids concentration conditions, i.e.,hodes et al. [30] used the high-speed video camera is capable ofecording the flow with Gs up to 80 kg/m2 s (Table 1), but are onlyestricted to the images at the riser wall.

In addition, almost all of the former studies appear to conducthe investigation within one type of particles, and very few refer-nces can be found clarifying the particle properties effects on theggregates characteristics, though Shi et al. carried out the experi-ent with different sizes of glassbeads, but no solid conclusion was

btained with regarding to the effects of particle properties. Sincerevious studies [13–15] have revealed that a strong dependence ofhe solids concentration and particle velocity on the particle prop-rties. Therefore, the particle properties, including particle density,ize and sphericity, may also play a non-negligible role in affectinghe characteristics of aggregations. The purpose of this study is tolarify the effects of particle properties on the particle aggregates
sing various types of particles with typical different density, sizend sphericity. To connect the two different measurements, intru-ive and non-intrusive, and make both function better, a high-speedideo camera and optic fiber probes were applied in a 2D circulatinguidized bed system in this study. It also realized the visualization Ta
ble

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378 J. Xu, J.-X. Zhu / Chemical Engineering Journal 168 (2011) 376–389

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Fig. 1. 2-D circulating fluidized bed unit and schematic of riser.

echnique to be effectively used under high solids concentration,here Gs is up to 200 kg/m2 s.

. Experimental apparatus

All experiments were carried out in a rectangular circulating flu-dized bed which was illustrated schematically in Fig. 1. The riser isrectangular column with a 7.6 m height and a 19 mm × 114 mm

0.75 in. × 4.5 in.) cross-section. The primary air at ambient tem-erature and pressure was supplied to the riser bottom through aerforated distributor. To avoid the misleading effects due to elec-rostatic forces, a small stream of steam was merged to control theumidity of the gas fed into the riser between 70% and 80%, which

s considered the optimal value required [35]. At the riser top, theolids passed through a smooth elbow into the primary cyclone foras-solid separation. Further solids separation was carried out by aecondary cyclone and a bag filter. The solids circulation rate wasegulated by a butterfly valve and measured by a device located athe top of the downcomer.

The reflective-type optical fiber probe is effective for mea-uring the local solids concentration in CFB risers, and has beenidely used by many investigators since its high accuracy and rel-

tively low cost [12,36–38]. It yields high signal-to-noise ratiosnd is nearly free from interference by temperature, humidity,lectrostatics and electromagnetic fields. Moreover, its small size
oes not significantly disturb the overall flow structure in CFB ris-rs if properly designed. The probe chosen to measure the localolids concentration in this study, PV6, was developed by Insti-ute of Process Engineering, Chinese Academy of Sciences. The.8 mm diameter probe tip consists of two bundles of optical fibres,
Fig. 2. Sketch of visualization system.

arranged precisely in vertical line. Each bundle of fibres has anactive area of 1 mm × 1 mm consisting of approximately 8000 emit-ting and receiving quartz fibres with a diameter of 15 �m for eachfiber. The emitted light reflected by the moving particles, and thenmagnified by a photo-multiplier and converted into voltage sig-nals. Since the relationship between the voltage signals and thesolids concentration in the measurement volume is nonlinear, areliable calibration is required to ensure an accurate measurement[12,36,37]. With precise calibration and cross-correlation appliedbetween the bundles of optical fibres, solids concentration and par-ticle velocity can be obtained. Details of the calibration process andcalculation of velocity were referred in the literatures [37,38].

The solids concentrations were measured at 9 lateral positionslocated at y/Y = −0.98, −0.75, −0.50, −0.25, 0, 0.25, 0.50, 0.75, and0.98, in which y/Y is the dimensionless distance from the riseraxis, and at 6 axial levels at Z = 1.27, 2.29, 3.30, 4.32, 5.33, and6.35 m, where Z is the distance from the riser distributor. To ensurethe validity and repeatability of sampled signals, 131,072 sets ofdata were taken at each position with a frequency of 100 kHz foreach measurement, which was repeated for at least 20 times. Thecross-sectional average solids concentrations were obtained byintegrating the local values at the 9 lateral positions. The instan-taneous solids concentration was analyzed by a self-developedFORTRAN program which introduces sensitivity analysis to identifythe clusters from solid concentration signals.

To eliminate the entrance and exit effects, the visualization sys-tem was mounted focusing on the upper fully developed region,where Z = 5 m. The system consists of alight source, a high-speedvideo camera and programs of digital image analysis (Fig. 2). Thelight source is 1000 W surface light diffused by one layer of diffuserpanel, which makes the recorded area uniformly illuminated andeliminates undesirable shadows and intensity gradients. The videocamera selected for the present investigation is the Redlake MotionScope M2 with a CMOS sensor. The camera in combination with theimage intensifier allows recording rates up to 16,000 fps and a max-imum resolution of 1280 × 512 pixel at 1000 fps. The device has abuilt-in storage leading to an observation time of 4 s at a frame rateof 1000 fps. Pentax C22516 25 mm lens was selected for recordingthe images of the whole column, while C21212 12.5 mm lens waschosen for capturing more specific images, i.e. images of riser cen-ter area or wall region. The high-speed video camera is connectedwith PC by 1394 Firewire, allowing the images captured to be mon-itored and the images recorded to be transferred to the computer.The image processing software, MotionScope 2.0.3, from Redlake,as well as self-developed Matlabprogram enable the image analysis
frame by frame.
The properties of the particles used in this study were listed inTable 2. The cumulative size distributions are shown in Fig. 3 .Thematerials were selected in order to investigate the effect of particlesize, density and sphericity respectively. FCC and Glassbead #1 have


Table 2Properties of particles used.

Particles FCC Glassbeads #1 Glassbeads #2 Glassbeads #3 Sand

Particle Sauter mean diameter (�m) 67 76 134 288 138Particle density (kg/m3) 1877 2453 2403 2498 2467Bulk density (kg/m3) 1125 1434 1421 1475 1453Sphericity 0.95 ∼1 ∼1 ∼1 0.65–0.75Particle terminal velocity (m/s) 0.26 0.42 1.19 3.73 N/A

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ractically the same size range and nearly the same particle Sauterean diameter (SMD) but different particle densities. Glassbeads1, #2, and #3 are in different size ranges but have the same par-

icle density and sphericity. The sand has much lower sphericityompared with Glassbead #2, while the particle size and densityemain close to it. The SEM images for Glassbead and sand par-icles are shown in Fig. 4. In this study, the solids concentration

easurement was conducted under the operating conditions ofg = 3–8 m/s, and Gs = 50–200 kg/m2 s, respectively. The high-speedlms were recorded at the corresponding operating conditions.

. Results and discussions

.1. Observation and description of clusters

Generally, the solids flowing in the riser were observed to dis-ribute dense in side-wall regions and dilute in the center. Thearticles were moving faster in the column center and slowerowards the wall. Nearly no evidence of solids buildup or falling-own was observed on both face walls. Though the experimentsere ran under wide range of operating condition, the clusters were

ften observed when Gs is 50–150 kg/m2 s and Ug is 3.5–8.0 m/s,hich agreed well with core–annulus flow regime proposed by

arlier studies [15,39]. Since the core–annulus structure is typi-ally found in the upper fully developed region [15,18], to visualizehe particle aggregates and identify the characteristics of clustersn circulating fluidized bed, we focus our study on the upper diluteegion, where the fully developed flow has been established. Thebservation is target to the wall and the center region respectively,o reveal the cluster forms and formation mechanisms in these twopecific regions.

.1.1. Clusters in wall regionFig. 5 shows sequence of four images of the suspension flow in

he wall region of the riser captured by the high-speed video cam-

Fig. 4. SEM images of Glassbead and sand particles.

era. The left edge of the image to the right is the left side wall of theriser (y/Y = −1) to the riser center (y/Y = 0) to 0, where “Y” is half ofriser width, “y” the lateral coordinate, the riser center is defined asthe origin of the lateral coordinate. A denser solids suspension con-centration can be observed clearly. The structure that high soildsconcentration near the side-wall and shed continuously to the risercenter can be recognized as “annulus”. Within the sequence of theimages, the annulus is seen to be compacted and several individ-ual clusters are formed, outlined as circled area in Fig. 5(c) and (d).According to the classification and description of the cluster formsby Bi et al. [19], the particle clusters (Clusters 1 and 2) and longishstreamer cluster (Cluster 3) can also be observed in the annulusregion. Bi et al. interpreted the motion of particles in the near wall
region and concluded that particles tend to migrate laterally fromthe core to the wall due to turbulent diffusion or saturation of gascarrying capacity in the core region. The compacted and clustersformed process near the wall shown in this study provide definiteevidence that the lateral particle segregation results in higher solids


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ig. 5. Sequence of 4 images taken in the core region with a dark structuredcale = 2.30 × 10−4 m/pixel, bed height Z = 5 m, lateral position y/Y = −1 to 0, superficp = 134 �m, �p = 2467 kg/m3, and ˚s ≈ 0.7.

oncentration in the wall region. Chan et al. [15] also indicated inheir study that the core–annulus structure may results from wallffects, which slow down the gas phase to allow formation of par-icle cluster. This interpretation can also be clarified by the currenttudy. Due to the wall effect, the slower motion of particles in theear wall region than in the riser center is clearly recorded by theigh-speed films. It is seen reduced gradually from the center axis,o almost stagnant on the wall. Occasionally, clusters in the formf particle swarm or sheet [19] are observed to fall down along theide wall. Fig. 6 exhibits a process of a denser cloud moving upwardn the riser center encounters a stream of cluster falling down onhe wall, which provides clear evidence that slower particle veloc-ty on the wall resulted from slower gas phase velocity contributeso the cluster formation.

Fig. 7 shows the formation of the annulus cluster. It can be seen
hat in Image (1) there exists a long strand cluster, which is usuallybserved in the core region of the riser [19]. The motion of particless found to have the strand cluster as boundary. From the columndge to the center, the particles in the area beyond the boundary
ig. 6. Sequence of clusters on the wall side (time interval between two pictures �t = 5 mosition y/Y = −1 to 0, superficial gas velocity Ug = 5.5 m/s, solids circulation rate Gs = 100 k

ter (time interval between two pictures �t = 20 ms, window pixel: 400 × 144,s velocity Ug = 5.5 m/s, solids circulation rate Gs = 100 kg/m2 s). The particle is sand,

move at high speed, while the particles within the wall area travelunder a very slow velocity which is correspondence to the veloc-ity of the cluster. Another stream of cluster appears on the lowerrighter quarter of Image (2). This cluster is partial of a U-shape clus-ter having a round “nose” facing upward. It seems that the U-shapecluster is “pushed” by the gas to move upward and expand its waketo adhere to the vertical strand cluster. Till the Image (6), the twostreams of clusters merged together and then move towards thewall, leading the solids in the wall area to further compacted. Theflow structure of high solids concentration in the annulus area andlow in the core region is generated. It can be seen that the clustersexisting in the riser build up the resistance to the gas and lead thegas to be re-distributed along the path with the least resistance,which is usually located along the riser center. Then the gas breaksthrough the clusters and has the potential to “sweep away” all the
particles blocking on its way. Grace et al. stated that the forma-tion of clusters observed in the riser center can be predicted bythe instability of gas–solids transport [40]. It can be concluded inthis study that the clusters in the riser center reinforce the insta-
s, window pixel: 256 × 880, scale = 1.99 × 10−4 m/pixel, bed height Z = 5 m, lateralg/m2 s).


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ig. 7. Sequence of clusters on the wall side (time interval between two pictures �osition y/Y = −1 to 0, superficial gas velocity Ug = 5.5 m/s, solids circulation rate Gs

ility of gas–solids transport and aggravate the generation of theore–annulus structure. The clusters observed in the core regionave the potential to transfer to the wall area and exist as clusters

n annulus region. In a word, the clusters observed in the annulusegion in this study are usually the clusters wake diffused from theore region (in strand cluster form) and streams of cluster fallingown on the wall. In addition, the small size particle clusters canlso be observed in the wall region under the operating conditionn this study.

.1.2. Clusters in center regionIn the center region, the U-shape cluster often can be observed.

ig. 8 shows an image sequence a typical U-shape cluster movingpwards in the center region of the riser. The frames (window sizef 46.6 mm × 13.5 mm) were taken at a recording rate of 2000 fpsnd an exposure time of 500 �s. The movement and development ofhe cluster can be recognized as the darker structure which is visu-lized directly within the observed area. The sequence of imageslearly show that a U-shape cluster is formed with a round “nose”acing downward and a core on the “nose tip”, where is mucharker than the peripheral area. Originally, the cluster is movings a longish core with blurred boundary. Continuously, the core istretched to be longer and crotched. Since the cluster is movinglower, the dispersed particles passing by are blocked and adhereo the cluster. Therefore, the U-shape outline is clearer and the cores darker and bigger with the aggregate of particles. Takeuchi et al.29] noted that the flow state of dense packets was chaotic buttrands with parabolic shape were relatively often observed. In this
tudy, the U-shape cluster is a typical form of particle aggregatesbserved in the riser center. In addition, though the structure ofhe cluster is variational, the cluster core is moving at a uniformelocity. With the analysis frame by frame, the velocity of clusteran be identified.
ms, window pixel: 256 × 880, scale = 1.99 × 10−4 m/pixel, bed height Z = 5 m, lateralg/m2 s).

In the center region, the clusters exist as the structures ofU-shape, longish strand and particle cluster. The pictures of theclusters are shown in Fig. 9. The U-shape is the most common struc-ture viewed in the riser center. Some of them have a core withparticular high solids concentration at the “nose tip”, while theothers do not. The opening of the U-shape cluster faces upward ordownward with a size range from 5 cm to 30 cm, most are smallerthan 20 cm. The upward U-shape clusters are observed to travelslower than the surrounding dispersed particles, while the down-ward move at comparable speed. The longish strand cluster is thecluster form also often observed in the core region of the riser.The size of the strand cluster is approximately 10 mm in width and10–50 cm in length. The motion of this form of cluster is seen obvi-ous slower than the vicinity. Occasionally, some clusters in smallsize (1–2 cm), and in shapes of circle, short stripe (as shown inFig. 9(c)) or crescent are observed. This type of particle aggregatesis classified as particle cluster by Bi et al. They are always seento flow as fast as the adjacent non-aggregate region. In addition,the shape of this type of cluster is recognized nearly constant dur-ing the motion in the observation window. Besides the forms ofindividual cluster aforementioned, clusters in different structuresmay adhere together to form floc-like clusters. The most commoncombination is seen between the U-shape and the strand clusters,typically shown in Fig. 9(d)–(f).

3.1.3. Proposed model predicting cluster formsBased on the observations in this study, a simple model is pro-

posed to interpret the formation of the four cluster forms mainly
observed in the center region, as mentioned in Section 3.1.2. If thereis no particle in the riser column, due to the wall friction, the distri-bution of gas velocity in a riser column is inherently higher in thecenter and lower towards the wall, as Fig. 10 shows. According tothe theory of energy minimization of gas–solids transport, the par-


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ig. 8. Sequence of 12 images taken in the core region with a U-shape cluster (tim= 5 m, lateral position y/Y = 0, superficial gas velocity Ug = 5.5 m/s, solids circulatios ≈ 1.

icles tend to distribute aggregatively as “clouds” after they enternto the riser, where the “cloud” is defined as the original form ofarticle aggregates. It is believed that the original size and densityf the “clouds” might be different and random, as the first schematichown in Fig. 10(a)–(d), respectively. The model claims that theres a balance between the “clouds” properties and the gas carry-ng capacity. The solids concentration and size of the clouds in thepstream are considered the main factors to determine the shapef the clusters downstream. If the solids concentration or the size ofhe clouds over balances with the capacity of the gas, deformationf the clouds might be observed. Fig. 10(a) shows the formation ofhe upward-facing U-shape cluster. The original particle cloud is
implified as a sphere with a denser core, of which the solids con-entration is considered overbalanced with the capacity of gas. Theigh density of the cloud core leads to a strong resistance to the gasnd results in a bypass for the gas to avoid the core (the darker color
ig. 9. Cluster structures observed in the riser center under different operating conditionsb) Glassbead #3, Gs = 100 kg/m2 s, Ug = 8 m/s; (c) sand, dp = 134 �m, �p = 2467 kg/m3, ˚s ≈ 0, Gs = 100 kg/m2 s, and Ug = 5 m/s; (e) Glassbead #1, Gs = 150 kg/m2 s, Ug = 5 m/s; (f) FCC, d

erval between two pictures �t = 10 ms, window size: 46.6 × 13.5 mm2, bed heightGs = 100 kg/m2 s). The particle is Glassbead #3, dp = 288 �m, �p = 2498 kg/m3, and

area). Therefore, a slower velocity of the cloud when compared withthe surrounding dispersed particles is observed. Only the solids onthe periphery of the cloud (the lighter color area) are diffused bygas to form the two “tails” of the “U” facing downstream, since thesolids concentration is comparatively lower than that in the cloudscenter. Thereafter, corresponding to the “wake theory” [19], the gaspasses the solids cloud drawing the vicinal particles to the low pres-sure region, which is behind the cloud, and condenses the core to ahigher concentration at the bottom of cloud. Such that the upward-facing U-shape clusters were often observed small in size and moveslower than the surrounding dispersed particles. Fig. 8 presents theentire formation process of this type of cluster. The second type is
as exhibited in Fig. 10(b). The size of the original cloud is consid-ered overbalanced with the gas carrying capacity though the clouddensity is not very high. Therefore, the gas is capable of propellingthe cloud at a speed comparable to the gas velocity. Attributing to
: (a) Glassbead #3, dp = 288 �m, �p = 2498 kg/m3, ˚s ≈ 1, Gs = 100 kg/m2 s, Ug = 5 m/s;.7, Gs = 100 kg/m2 s, Ug = 5 m/s; (d) Glassbead #1, dp = 76 �m, �p = 2453 kg/m3, ˚s = ∼p = 67 �m, �p = 1877 kg/m3, ˚s = 0.95, Gs = 100 kg/m2 s, and Ug = 5 m/s.


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Fig. 10. Proposed model for the for

he inherent distribution of gas velocity, the big size of this type ofloud leads to a slower velocity of the particles on the two edgesnd forms the two “tails” facing downward. Based on this inter-retation, the reason for the downward-facing U-shape clusters issually observed large in size and without particular high concen-ration core has been clarified. Fig. 10(c) presents the formationf the strand cluster originating from the small and low densityloud. The overall density of the cloud is within the capacity of theas and leads the gas to diffuse and stretch the cloud to be longish.he fourth form is the particle cluster which exists unchanged inhape for a long period of time. Fig. 10(d) shows that the origi-al cloud is high in solids concentration and small in size. The gas
treams could carry the entire cloud at a slower speed and with-ut stretching the shape of the cloud. This type of cluster is easyo be identified and traced in the riser for the analysis of clusterelocity.
n of different structures of cluster.

3.2. Observation and comparison of particle properties effects oncluster forms

Five different types of particles were employed in this study. Theeffects of particle density, size and sphericity on the clusters behav-iors were compared. Fig. 9 lists sorts of clusters in the riser centeroperated with different particles under several typical operatingconditions. All the images are in the size of 256 pixel × 880 pixelwith a scale of 1.99 × 10−4 m/pixel. The influence of the operat-ing condition on the forms of clusters cannot be identified fromthe images, whereas, the cluster structures seem to be affected bythe particle velocity significantly. In Fig. 9(a) and (b), Glassbead #3
with a mean size of 288 �m is seen to form clusters typically in U orstrand shape and with a large cluster size. The sand particles having134 �m and 0.7 sphericity are observed to have the flow structureindistinguishable from the Glassbead #3, while small size clusters

384 J. Xu, J.-X. Zhu / Chemical Engineerin

0 50 100 150 200 250 300 350 400

0.0

0.2

0.4

0.6

0.8

1.0

FCC, y/Y = 0

FCC, y/Y = 0.5

FCC, y/Y = 0.98

GB #1, y/Y = 0

GB #2, y/Y = 0

GB #3, y/Y = 0

Sand, y/Y = 0

La

rge

siz

e c

luste

r fr

actio

n

U = 5.5 m/s

G = 100 kg/m2s

Ns = 30

g

s

ctciwiGcuocmvicalb

3

rtbluscot2bmccfh

ibdtsci

Ns

Fig. 11. Cluster number fraction vs. Ns .

an be found occasionally. With further decreasing of particle sizeo 76 �m for Glassbead #1, the form of clusters turns to be compli-ated and multi-structured. It is seen that the clusters are smallern size than that of the larger particles, and tend to connect together

ith each other. Therefore, the individual cluster is difficult to bedentified in small size particles flow. Compared with the flow oflassbead #1 (2453 kg/m3), the structure of clusters is more intri-ate and irregular when lighter FCC particles (1877 kg/m3) weresed, as shown in Fig. 9(f). The area with darker color, where isccupied by the clusters, is obviously larger than the area in lighterolor. In other words, there are great amount of particles are seenoving in aggregating form and few particles are left to move indi-

idually. The size and form of individual cluster is unlikely to bedentified since the interconnection among the highly populatedlusters is very intense. The observation indicates that the smallernd the lighter particles have higher potential to aggregate than thearger and heavier particles. The effect of particle sphericity cannote distinguished here.

.3. Characterizing clusters with optical fiber probe

To identify clusters with reflective probes applied, a set of crite-ion must be satisfied. Based on the previous studies, it is suggestedhat [23,41]: (1) the solids concentration inside the cluster muste n-times the standard deviation of the sampled signal over the

ocal time-mean solids concentration; (2) the number of consec-tive samples above the critical solids concentration, Ns, must beet to determine the minimum time interval for the perturbationaused by a cluster; (3) the sampling volume must be greater thanne to two orders of particle diameter. In the current study, sincehe riser is narrow rectangular column, which is considered as aD CFB, the solids concentration obtained in this CFB system haseen compared with 3D CFBs data from the literatures. Further-ore, it is found in this study that the sampling frequency of solids

oncentration signal is another sensitive criterion to establish theluster properties. Compared with the literature data, the samplingrequency in this study is placed very high, 100 kHz, which allowedigh sensitivity to the solids concentration.

Subjecting to the difference of sampling frequency among var-ous studies, the optimal values for both n and Ns are required toe determined individually. The sensitivity analysis, firstly intro-
uced by Manyele et al. [23], is adopted in this study to optimizehe value for n. Therefore, n = 2 as the standard deviation of theampled time–mean solids concentration is finalized as optimalritical solids concentration. Then such method is improved todentify Ns. The cluster number fraction, Flc, is newly proposed,
g Journal 168 (2011) 376–389

where Flc = Nlc/Nc, where Nc is the total number of the clusters withthe solids concentration higher than the critical value over the timeseries studied, while Nlc is the number of clusters with Ns consec-utive samples above the critical solids concentration. Consideringthe cluster number fraction as a sample parameter for the sensi-tivity analysis, an increase/decrease of Ns would lower/raise thefraction of clusters with existence time longer than Ns samplingtime interval. Some of the perturbations of solids concentrationare very small and with short time intervals, therefore, they aresupposed to be classified as dispersed particulate phase. Sincesuch small perturbations are numerous, there tends to be a sharpdecrease of Flc when the set Ns value is increased beyond the valuethat demarcates the particulate phase and the clusters. In otherwords, there should be a sharp drop of Flc with increasing Ns.Compared with the method Manyele et al. originated, the most sig-nificant difference is taking Flc into account, instead of the clustertime fraction, Fc. Since for different types of particles, the clustertime fraction is significantly variable. It is very difficult to unify theoptimal value of different particles under wide range of operatingconditions. With the scaling of Nlc/Nc the sensitivity analysis of Ns

for sorts of particles are well normalized, and the optimal value orNs under specific operating condition is unique, as plotted in Fig. 11.The criteria set for this study and the literature data are listed inTable 3.

3.3.1. Cluster number fractionIt is found that the cluster number fraction, Flc, can not only

be used to determine the optimal value for Ns, but also character-ize the effects of particle properties on the aggregates. Since Ns isthe number of consecutive samples, with a sampling frequency, itcan be easily transferred to the minimum time interval, Tc, set forthe perturbation caused by a cluster. Fig. 12 plots Flc against min-imum time interval to elucidate the aggregates characteristics ofdifferent particles. Fig. 12(a) interprets the fractions of cluster num-ber at different lateral positions. The Flc at the riser center region(y/Y = 0), middle region (y/Y = 0.5) and wall region (y/Y = 0.98) areseen decreasing with the increase of minimum time interval. Inother words, with increasing minimum time interval set for a clus-ter, the number of clusters with the transit time longer than thecriterion decreases. It can also be seen that the decreasing curvesfor the center region (y/Y = 0) and the region between center andwall (y/Y = 0.5) are almost overlapping and cross approximately atTc = 1.1 × 10−3 �s. Below this value, the cluster number fraction aty/Y = 0 is larger than that at y/Y = 0.5, while smaller when beyondthe point. The curve for the wall region with y/Y = 0.98 is obviouslyabove the other two, meaning that the population of clusters in thewall region is larger than that in the center or middle region. Dueto the wall friction, the particle velocity is low on the wall, whichincreases the tendency of forming clusters and the probability ofexistence for clusters. Fig. 12(b) compares Flc of particles with dif-ferent mean size. It is found that under identical Tc, the Flc of smallersize particles is greater than that of larger particles. It means thatthe finer particles are prone to aggregates and incline to form clus-ters. It is agreed well with the observations in Section 3.2. The finerparticles (GB #1or FCC particles) were seen to form numerous clus-ters interconnecting with each other, while only several huge sizeclusters were observed occasionally in the coarse particles (GB #3or sand). For the particles with different density, the curves of Flcagainst Tc cross approximately at Tc = 0.55 × 10−3 �s, as the dottedline shows in Fig 12(c). Under the small time criterion is set, thefraction of clusters number for FCC particles is larger than that of
GB#1. With the increase of Tc, the clusters for heavier particles (GB#1) are greater in fraction than for lighter particles (FCC) when Tc
passes over the marked dotted line. It indicates that the lighter par-ticles tend to form smaller clusters than the heavier particles. It ismatched with the observations by high-speed films in Section 3.2.


Table 3Literature data on the criteria used in establishing cluster properties.

Author(s) Soong et al. [41] Tuzla et al. [42] Manyele et al. [23] This study

Measurement technique Needle capacitance probe Needle capacitance probe Reflective optical fiber probe Reflective optical fiber probeSampling frequency (kHz) 5 5 0.97 100n 3.0 2.0 1.0–1.4 2.0Ns N/A N/A 3 25Operating conditions Ug = 5.0 m/s, Gs = 45 kg/m2 s Ug = 5–6 m/s, Gs = 89 kg/m2 s Ug = 5.5–10 m/s, Gs = 100–550 kg/m2 s Ug = 3.5–8.0 m/s, Gs = 50–200 kg/m2 s

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0

0.0

0.2

0.4

0.6

0.8

1.0

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0

0.0

0.2

0.4

0.6

0.8

1.0

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0

0.0

0.2

0.4

0.6

0.8

1.0

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0

0.0

0.2

0.4

0.6

0.8

1.0

←Tc=1.1×10

-3μs

Larg

e s

ize c

luste

r fr

action,

Flc

FCC, y/Y = 0

FCC, y/Y = 0.5

FCC, y/Y = 0.98

Ug = 5.5 m/s

Gs = 100 kg/m

2s

(a) (b)

GB #1 (dp = 76μm), y/Y = 0

GB #2 (dp = 138μm), y/Y = 0

GB #3 (dp = 288μm), y/Y =0

Z = 5.33 m

(d)(c)

FCC (dp = 1877kg/m3), y/Y = 0

GB #1 (dp = 2453kg/m3), y/Y = 0

Larg

e s

ize c

luste

r fr

action,

Flc

−3 −3

← ←Tc=0.55 × ×10

-3μs Tc=0.45 10

-3μs

GB #2 (Φs = ª1), y/Y = 0

Sand (Φs = ª0.7), y/Y = 0

fractio

TibplBcpto

Minimum time interval, Tc, (× 10 μs)

Fig. 12. Cluster number

he curves for particles with different sphericities are also observedn Fig. 12(d) when Tc = 0.45 × 10−3 �s. Same interpretation can alsoe applied to the different sphericities particles: the more sphericalarticles incline to aggregate larger size clusters than the irregu-

ar particles when Tc is beyond the value of the intersection point.
elow the marked line, the two curves are nearly overlapping, indi-ating that the clusters fraction in each size cut for both types ofarticles are almost the same. In other words, the sphericity of par-icles has only minor effects on the small size clusters but morebvious on the larger size aggregates.
Minimum time interval, Tc, (× 10 μs)

n for different particles.

Since the clusters are irregular in shape and vary both later-ally and axially within a riser, the accurate definition of the clustersize is impossible. Therefore, the vertical length is usually usedto identify the size of clusters. Because the time interval of thesolids concentration perturbation measured by the optical fiber
probe represents the traveling time of a cluster passing througha probe tip, it is feasible to calculate the cluster vertical lengthwith dvl = Vc × Tc, where Vc is the vertical velocity of cluster [43].With the evaluation of the cluster velocity, it is possible to obtainthe size of clusters in the riser. Consequently, the cluster num-


0.00 0.25 0.50 0.75 1.00

0.0

0.2

0.4

0.6

0.8

1.0

0.00 0.25 0.50 0.75 1.00

0

2

4

6

8

10

0.00 0.25 0.50 0.75 1.00

0

25

50

75

0.00 0.25 0.50 0.75 1.00

0

2

4

6

8

10

12

14

16

FCC

GB #1

GB #2

GB #3

Sand

F,

noit

carf

re

bm

un

ret

sul

Clc,

(-)

Reduced lateral position, y/Y (-)

Ug = 5.5 m/s

Gs = 100 kg/m

2s

Z = 5.33 m

Ns = 30

Clu

ste

r tim

e fra

ction, F

c (

%)

Reduce lateral position, y/Y (-)

Clu

ste

r fr

equency, f c (

Hz)

Mean c

luste

r exis

tence t

ime,

τ c (

ms)

ferent

bs

3

(mhruw

3dvmtstTs


Fig. 13. Characteristics of clusters for dif

er fraction, to some extent, reflects the distribution of clusterize.

.3.2. Particle properties vs. cluster characteristicsThe cluster characteristics investigated in this study include:

1) the cluster time fraction, Fc; (2) the cluster frequency, fc; theean cluster existence time, �c. The definitions of these parameters

ave been stated by Manyele et al. [23]. Fig. 13 shows the summa-ized results of the cluster properties for the five types of particlesnder the operating condition of Ug = 5.5 m/s, Gs = 100 kg/m2 s,hile Fig. 14 is the result obtained under Gs = 200 kg/m2 s.

.3.2.1. Cluster number fraction, Flc. The cluster number fractionisplays the number fraction of the cluster with long time inter-al. In other words, the larger the cluster number fraction is, theore clusters with long time interval exist. For all types of par-

icles, the lateral profiles of the cluster number fraction, Flc, arehown in Fig. 13(a), Flc is seen to increase along the lateral direc-ion, approaching a maximum, then decrease towards the wall.he cluster number fraction is low in the core region where theolids concentration is low, which contributes to less interconnec-


particles (Gs = 100 kg/m2 s, Ug = 5.5 m/s).

tion force between particles and leads to smaller size of clusters.The peak point near the wall is attributed to the strong gas–solidinteractions in the core–annulus interface. For different types ofparticles, it can be seen that the lateral increases of Flc for the lighter(FCC) and finer (GB #1) particles are more significant than for theheavier and courser particles (GB 2, 3 and sand). It means that thewall friction does more significant effect on the lateral distribu-tion of particle clusters. Similar observation can be obtained underdifferent operating condition when Ug = 8.0 m/s, Gs = 200 kg/m2 s.Under Ug = 8.0 m/s, the cluster number fraction of heavier particlesis higher than that of the lighter particles. The smaller the particles,the larger the cluster time fraction, which can also be applied to thecondition of Ug = 8.0 m/s.

3.3.2.2. Cluster time fraction, Fc. Fig. 13(b) shows the lateral profilesof the cluster time fraction for the five types of particles. It can be
seen that the profiles are very uniform, suggesting that the parti-cle aggregation is uniform along the lateral direction. However, itis found that there exists a severe high cluster time fraction in theannulus reported by Manyele et al. [23]. It means that the particleaggregation in the annulus is much more severe than the results


0.00 0.25 0.50 0.75 1.00

0.0

0.2

0.4

0.6

0.8

1.0

0.00 0.25 0.50 0.75 1.00

0

2

4

6

8

10

0.00 0.25 0.50 0.75 1.00

0

25

50

75

0.00 0.25 0.50 0.75 1.00

0

2

4

6

8

10

12

14

16

F,

noit

carf

re

bm

un

ret

sul

Clc,

(-)


Ug = 5.5 m/s

Gs = 200 kg/m

2s

Z = 5.33 m

Ns = 30

FCC

GB #1

GB #2

GB #3

Sand

Clu

ste

r tim

e f

raction,

Fc (

%)


Clu

ste

r fr

equency,

f c (

Hz)

Mean c

luste

r exis

tence t

ime,

τ c (

ms)

ferent

occftgtGa

3qccprltotiu



btained in this study. This is understandable given the solids con-entration profile of this study, which is more uniform than that ofylindrical risers. The plot also shows that the cluster time fractionor the lighter (FCC) and smaller (GB #1) is higher, which indicateshat the lower particle density contributes to more particle aggre-ation. The same also applies to the smaller particle size, havinghat the smaller the particles, the more aggregation form. Unders = 200 kg/m2 s, the cluster time fraction profiles remain the sames the results of Gs = 100 kg/m2 s.

.3.2.3. Cluster frequency, fc. The lateral profiles of cluster fre-uency are plotted in Fig. 13(c). Along the lateral direction, theluster frequency is observed decreasing towards the wall. Therean be seen a “trough” of the lateral profiles for some types ofarticles near the wall. The low cluster frequency is consideredesulting from the formation of large size clusters. The effect ofocal mean solids concentration is competing to form more clus-
ers or to increase the cluster size, while reducing the numberf clusters. In this study, the cluster size is believed larger nearhe wall and smaller in the core region. That is the reason resultsn the lower cluster frequency towards the wall. It is seen that,nder Gs = 100 kg/m2 s, the cluster frequency of FCC particle is


distinct higher than the others heavier particles. While underGs = 200 kg/m2 s, the cluster frequency of GB #1 is the highest.The decrease tendency of the lateral profiles towards the wall ismore significant than that under Gs = 100 kg/m2 s, which might bedue the relatively high solids concentration on the wall region forthe conditions of Gs = 200 kg/m2 s. The results of cluster frequencyalso indicate that the lighter and smaller particles have more ten-dency to aggregate than the larger and heavier particles, while thesphericity of particles does limited role in affecting the cluster fre-quency.

3.3.2.4. Mean cluster existence time, �c. To verify the lower clusterfrequency results from the larger cluster size, the mean cluster exis-tence time is plotted Fig. 13(d). It can be seen that, generally, thelateral profile of �c is opposite to the profile of cluster frequency. Inother words, the lower the cluster frequency, the longer the cluster
exists. The lateral profile of �c has a general tendency of increasingtowards the wall, with more significant increase under higher Gs.The cluster existence time under Ug = 8.0 m/s (Fig. 15) are generallyshorter than under lower superficial gas velocity, which might bedue to the higher cluster velocity.


0.00 0.25 0.50 0.75 1.00

0.0

0.2

0.4

0.6

0.8

1.0

0.00 0.25 0.50 0.75 1.00

0

2

4

6

8

10

0.00 0.25 0.50 0.75 1.00

0

25

50

75

0.00 0.25 0.50 0.75 1.00

0

2

4

6

8

10

12

14

16

F,

noit

carf

re

bm

un

ret

sul

Clc,

(-)


Ug = 8.0 m/s

Gs = 200 kg/m

2s

Z = 5.33 m

Ns = 30

FCC

GB #1

GB #2

GB #3

Sand

Clu

ste

r tim

e f

raction,

Fc (

%)


Clu

ste

r fr

equency,

f c (

Hz)

Mean c

luste

r exis

tence t

ime,

τ c (

ms)

ferent

4

ragFspitp

cwprt



. Conclusion

The particle aggregation characteristics were studied in a nar-ow rectangular CFB riser with a 19 mm × 114 mm cross-sectionnd a 7.6 m length. The study was conducted by operating FCC,lassbeads and sand particles under various operating conditions.orms of clusters were observed by employing a visualizationystem with a high-speed video camera. The lighter and smallerarticles were seen to have more tendency to aggregate and form

nterconnected clusters, while the effects of particle sphericity onhe cluster form are unapparent. A new model was developed toredict the cluster forms in the fully developed region.

The aggregation characteristics were also studied with the opti-
al fiber probe. Several properties of clusters were investigatedith the solids concentration signals obtained by the probe. Thearameter of the cluster number fraction was first defined. Theesults obtained by analyzing the instantaneous solids concen-ration agreed well with the observations and also indicate that


the low particle density and small particle size contribute to formclusters. It shows that the particle sphericity plays limited role inaffecting the particle aggregation.

To summarize, it can be concluded that with the visualizationand sensitivity analysis, some important characteristics of clusterhave been determined and the effects of particle properties on par-ticle aggregation have been generally revealed. In future study, thecluster vertical length and velocity might be determined by ana-lyzing the instantaneous solids concentration signals and the highspeed video images. The effects of particle properties on cluster sizeand velocity might also be identified. The determination of clus-ter characteristics in the current study associated with derivationof cluster size and velocity may contribute to the overall particle
velocity, particle residence time distribution in CFB and add valueto the practical CFB engineering design.
The findings of cluster size and velocity will be integrated withthe distribution of particle velocity and solids concentration whichhave already been determined by earlier work in the same riser to

eerin

fis

R

[

[

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[fluidized bed, in: Circulating Fluidized Bed Technology IV, AIChE, New York,

J. Xu, J.-X. Zhu / Chemical Engin

urther elucidate the mechanisms of particle aggregation influenc-ng on the instantaneous solids distribution and formation of flowtructure.

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Documents

Visualization of particle aggregation and effects of particle properties on cluster characteristics in a CFB riser