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The application of computer-based imaging to the measurements of particle velocity and voidage profiles in a fluidized bed
POWDER TECHNOLOGY ELSEVIER
Powder Technology 98 ( 1998 ) 183-189
The application of computer-based imaging to the measurements of particle velocity and voidage profiles in a fluidized bed Bram A. Saadevandi i, Richard Turton * Deportment t!f Chemh'al Engineering, West Virginia University, P.O. Box 6102, Morgantown, WV 26506-6102. USA Received 9 March 1998
Abstract Computer-based video imaging techniques were utilized in order to measure the axial and radial components of particle velocity and voidage profiles in the draft tube region of a semi-circular spouted fluid bed coating device. Computer images were obtained using standard RS- 170 video signals ( 30 frames/s) from an image processing board and a CCD variable shutter speed camera. When measuring particle velocities. low shutter speeds of I-2 ms were utilized. Due to rapid motion of particles, the images obtained were blurred streaks several millimeters in length. The length and direction of streaks were proportional to the magnitude and direction of the projected velocity vector. By using dispersed back lighting, the particle velocity images appeared as light streaks on a dark background. Custom software was written in order to automatically search for and to identify bright streaks and calculate particle velocities. The velocity measurements obtained from the software were compared with data taken with a high speed Kodak video system ( 1000 frames/s with a 20-p,s strobe). The results were in close agreement. The video images for analysis of voidage measurements were obtained using the same techniques as for the velocity measurements except with a shutter speed of 0. i ms. The images thus obtained showed the particles to have a dark outer ring with a light center. The search algorithm for identifying particles involved establishing the gray level for nine different locations: eight compass points and a center point. By searching the frame for the presence of particles, and then comparing the gray levels at the circumference and the center of the particle image it was possible to distinguish between in-tbcus and out-of-focus particles. A comparison of the results using the software with those of standard models made with glass beads, and by visually counting the particles, was in close agreement. © 1998 Elsevier Science S.A. All rights reserved. Keywords: Computer-based imaging: Particle velocity; Voidage proliles: Fluidi,,.ed bed: Axial component: Radial component
I. Introduction Studies of the hydrodynamics of fluid bed coating devices are essential in order to predict and scale-up the performance of commercial-scale units from results obtained in smallscale laboratory equipment. Investigations by Cheng and Turton [ I ], on the uniformity of particle coating in a draft tube spouted bed of I mm diameter particles, have shown that the hydrodynamics in the spray zone is the dominant factor affecting the unilbrmity of particle coating. Information on particle velocity and voidage profiles in the spout and annular regions as well as in the spray zone of these beds is vital to the understanding and prediction of bed perlbrmance. There have been numerous methods of measuring the velocity of particles and voidage in gas-solid fluid systems. * Corresponding author. Tel.: + 1-304-293-211 ! ext. 415: Fax: + 1-304293-4139; E-mail: [email protected] Present address: General Electric, GE Plastics. P.O. Box 68, Washington, WV 26181. USA. 0032-5910/98/$19.00 © 1998 Elsevier Science S.A. All rights reserved. Pll S 0 0 3 2 - 5 9 ! 0 ( 98 ) 0 0 0 5 6 - 4
A review of these methods is given by Cheremisinoff 121. Cinephotography has been one of the major techniques used for studying the hydrodynamics of particles in a ftuidized bed. However, photography is a very time consuming technique, even with a digitizer to aid analyzing panicle coordinate data. Framing frequencies of 2000-3000 Hz were utilized by several investigators to measure particle velocity in the spout region 13-51. Other techniques such as radioactive tracer, laser Doppler anemometry, 7-ray emission and fiber optic probes have been used to measure panicle velocities in a spouted bed 16-91. Some of the techniques, which were mentioned above, have also been employed to measure voidage in fluidized beds. Lefroy and Davidson 1101 employed a direct photographic technique to measure the voidage profile in a spouted bed column. This technique consisted of photographing the spout, in a semi-circuhn column. and comparing the number of particles per unit area with a number in a similar area of the packed bed annulus, for which the voidage was known. He et al. ! II I recently used a fiber
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B.A. Saadevandi, R. Turton / Powder Technology 98 (1998) 183-189
optic probe to measure voidage profile in a full and half spouted fluid beds. This paper describes the application of computer-based video imaging, to measure particle velocity and voidage profiles in a spouted fluid bed coating device. This technique is non-intrusive and is shown to be capable of providing reliable particle velocity and voidage profiles in the spout.
2. Experimental equipment and procedure The experimental equipment used in this research is shown schematically in Fig. ~ The apparatus consisted of a semicircular spouted bed with a draft tube insert. The bed was 22,9 cm (9 in.) in diameter and 59.7 cm ( 23.5 in.) high and the draft tube insert was 10.2 cm (4 in.) in diameter and 35.6 cm ( 14 in.) high. The bottom of the draft t~lbe was angled at 60 ° from horizontal as shown in Fig. I, insert A. This moditication reduced the flow of particles towards the spray nozzle and assisted the particle flow pattern upward through the spray zone. The draft tube was pressed onto the fiat front lace of the bed using spring-loaded bolts located at the back of the bed. This design allowed the draft tube to be adjusted easily up or down relative to the distributor plate. The major portion of the bed was made from transparent Plexiglas with a transparent glass front face, 6.35 mm thick. The whole assembly was bolted to a metal frame. The distributor plate consisted of a 316L stainless steel sintered plate, 2.4 mm thick with 100/.tm pores, which separated the bed from a split plenum. In order to operate with maximum flexibility the lower portion of the bed ( plenum chamber) was split into an inner and outer section with independent air supplies to each region. The fluidizing air was supplied by two centrifugal blowers in series and regulated through rotameters prior to entering the central and annular regions of the bed. Finally, the bed was equipped with a semi-circular spray nozzle located at the center of the distributor plate and at the Ih)nt face of the equipment, The spray nozzle was an air atomizing type with an air cap in which a coating liquid was sprayed into the bed Top Views
......
Veal to Atmosphere Front View 4
no,-,et a'i"o"P"Y
Side View
using compressed air as the atomizing fluid. For this work the air cap was cut in half and adapted to fit the spray nozzle so as to provide an 180° spray pattern using three orifices. Water was used as a model spray liquid and spray conditions were chosen so as to avoid any agglomeration of particles during the experiments. The whole equipment was essentially a typical small scale fluid bed coating apparatus cut in half. The basic experimental principle in this work was to acquire computer images using a standard RS- 170 video signal (30 frames/s) from an image processing board and a camera. In this study the movement of closely sized glass beads (dp= i.086 mm and po = 2500 kg/m 3) was observed through the front face of the semi-circular fluid bed using a charged couple device (CCD) variable shutter speed camera ( Pulnix TM-7CN equipped with a C-mount 50 mm Fuji lens with aperture f/I.4 attached to a 20-ram extension tube). Customized software was developed una automated to interpret the computer-based digitized images through an image processing board ( Data Translation's DT-385 I- I with display resolution of 640 × 480) and used to measure particle velocity and voidage proliles at the front face of the fluidized bed. When tracking an object using an RS-170 video signal, a problem arises during frame grabbing that is known as interline blurring. A frame consist of two fields (even and odd lieids) which are taken 16.7 ms (60 ~ ~ s) apart. Thus two consecutive fields are spliced together to form a single frame. Since the intbrn~ation in a frame is made up I'rom images that are 16.7 ms apart, the resulting inlormation is smeared. To alleviate this problem, the even and odd lields of a single frame are split apart prior to analyzing pixel data. By splitting the frames one obtains a clearer, sharper image, although the vertical resolution per field is reduced by a factor of two, while the horizontal resolution is unafl'ected. In this work, only the even lields were analyzed. in the current work, the framing rate is not of great importance since, as will be shown later, both voidage and velocity data are obtained from a single lield. However, it is also possible to analyze the odd lields and this would allow video measurements to be obtained at an effective framing rate of 60 Hz. if particle-tracking algorithms were to be implemented, then the use of a higher effective framing rate would be of importance. Finally, the hghting arrangement is also a very important aspect of this technique, and must be optimized with respect to the equipment geometry and particle loading in the bed.
Monitor
2. I. Calibration tecimique fiJr depth o.lifield
~
IC~lial~ Solution
.
•
"L I'l~l ~
FrameGrabber
-~
Fig. I. Schematic diagram of fluidized bed and video imaging system.
In order to t~valuate wall effects, which arise from the gaswall and particle-wall interactions, the particle velocity and voidage measurements were carried out at the front wall and at a distance in from the wall's surface. Hence, it was necessary to develop a calibration technique to determine precisely the field of view and depth of field of the optical system and the exact location of the measurements during the exper-
185
B.A. Saadevandi, R. Turton / Powder Technology 98 (1998) 183-189
Thin Transparent Thread
Thin Acrylic Sheet (0.$ mm thick)
N y l o n ~I.I.I.I.I,I,N
Spotlights
White Screen
(300 art e a e h ) ~ T i Fluidized Bed ~ (Top View)
I00 cm 50 c
Camera
Fig. 3. Dispersed back lighting arrangements. Glass Partic es
(!.086 mm diameter) Fig. 2. Diagramof standard sample for testing depth of field of camera and standard sample set-up in fluidizedbed.
iments. For this purpose, standard samples were constructed from the same glass particles used in the experimental work, Fig. 2. Glass particles were glued to the surface of several layers of thin transparent acrylic sheets (thickness=0.5 mm), and placed inside the dral't tube of :t second identical semi-circular bed (same dimensions as the original bed) against the fiat wall's surface. Additional particles were attached to several thin rods positioned vertically in the background (inside the draft tube) so as to simulate the lighting conditions in the actual bed, see Fig. 2. During an experimental run, a portion of the dispersed back lighting will be adsorbed by the particles in the background due to the dynamic environment. By placing the rods in the background during the calibration experiments, it was possible to simulate the lighting conditions occurring when the actual bed is running. The depth of field was determined by tbcusing on the first layer of particles of a standard sample ( Fig. 2) located at the wall, and moving to each successive layer of particles until the previous layer became slightly out of locus. In addition, each layer's peak Ibcusing point was precisely marked on the lens lbr proper depth calibration from the wall's surface. Using these techniques, the depth of field of the camera was measured to be 5.0 mm, details of the field of view calibration and the pixel-length conversion lbr particle velocity and voidage are given elsewhere I 121.
2.2. Voidage proJile measurements hi the dra/'t tube in order to estimate the radial and axial voidage profiles, the camera was tbcused on an I cm by I cm area in the draft tube. The camera was focused approximately 3 mm inside the glass front lace of the bed. A fast shutter speed of 0. ! ms was utilized to capture clear images of particles in the draft tube. This analysis of voidage was for a 1 cm by i cm by 0.5 cm volume region. The voidage measurements were obtained by taking a series of images of the bed. Customized software was written to automatically identify and count the number of particles in a given volume equal to the field of view multiplied by the depth of field of the optical system. As was explained earlier, in order to eliminate the interline blurring once a frame of video was acquired, the even field
Particle ImagesObtained using Dispersed Back Lighting (bright center and dark annular ring)
O:
IoOOo 8 Compass Points and Center Point Location for Particle Search Algorithm
Fig. 4. Diagramshowingtypicalfieldobtainedduringvoidagemeasurements and the location of test pixels used in particle identification.
was stripped numerically from it. The main function of the software was to count the number of particles that met all the test criteria within a region of interest in a field. This was established with a main loop that counted down through each row of video data. Within each iteration of the main loop a secondary loop was used to step through a row looking for every third pixel in that row. By utilizing the dispersed back lighting arrangement (Fig. 3) the images of the particles showed a dark outer ring with a bright center (Fig. 4). Thus at every third pixei in a field the software established an analysis of the brightness value of nine pixels. These pixels included eight equally spaced points around the circumference and a point at the center of the pattern. The distance of the center point from the compass points was determined based on the average radius of the glass particles convened to the appropriate number of pixels. Once the nine points were established, two test were applied by the software in order to determine whether a point is at the center of the particle. First, the software counted how many of the eight pixels fell below a given gray scale (0 to 255, black to white) value. If six or more points qualified, then the software proceeded to the next test. Second, the software counted how many of the eight pixels had more than a certain threshold difference with the center pixel. If six or more points did, then panicle was determined to be in focus. In essence, only in-focus particles were counted in the determination of the voidage. In order to confirm the above strategy, standard samples with known voidage were made from glass beads (the samples which were described in Section 2. I for calibration tech-
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B.A. Saadevandi, R. Turton / Powder Technology 98 (1998) 183-189
Table ! Comparison of results obtained for voidage at the same location and at the same operating conditions using the video imaging system and software Sample size (N)
Average voidage + 95% CI
100 100 100 ! 00
0.897 + 0.007 0.899 4- 0.006 0.895 4- 0.007 0.893 4- 0.007
niques, see Fig. 2). The standard samples were placed inside the draft tube of a second identical semi-circular bed against the front wall surface (Fig. 2). Using standard samples with known voidage, within the given depth of field, 5 mm, and the dispersed back lighting arrangement, known voidage values for each sample and the voidage given by the software were compared. There was close agreement between the measured voidage by the software and the known voidage calculated for each sample. The idea here was to demonstrate that the voidage values given by the software were correct, and corresponded to the number of in-focus particles within the depth of field of the camera. In addition, the reproducibility of measurements taken by the imaging software, at a particular location and at the same conditions was investigated. A comparison of the mean voidage calculated by the software for replicated experiments at the same conditions showed that the mean voidage values were in good agreement with each other, as shown in Table I. Therefore, repeated measurements at different solids Ioadings were used to obtain statistically significant estimates of the voidage at a given location and set of operating conditions. Due to the ability of the software to discriminate in-focus and out-of-locus particles, the particle count within the field of view is a direct measurement of the voidage within a bed volume of I cm × I cm X 0.5 cm (field of view x depth of field).
2.3, Particle velocity prt!/ile measurements in the drt!/'t robe Particle tracking software was developed and automated to carry out the radial particle velocity profiles at different axial locations above the distributor plate in the draft tube region of the bed. A similar technique as described above for voidage profiles was utilized to measure particle velocities. Shutter speeds of I to 2 ms were determined to be the most appropriate for the range of particle velocities in the draft tube. By reducing the shutter speed and by utilizing dispersed back lighting, Fig. 3, images were produced that were bright streaks on a dark background ( Fig. 5). The lengths of streaks, typically several millimeters, are directly proportional to the local speed of the particle. Also the direction of a streak is an accurate measurement of a particle's velocity (U,) in twodimensions (U, and U=). Customized software was written to automatically identify a particle streak and to measure the length and direction of the particles" movement. As in the case of the voidage measurements, only even fields of frames were analyzed. The even fields were searched
Location of Dark-Bright Transitions used to Identify Particle Streaks
/ Particle Traces using Slow Shutter Speed (bright streaks on a dark background) Fig. 5. Diagram showing typical field obtained during velocity measurements, the location of test pixels used in streak identilication and the coordinate system adopted.
in order to identify qualified bright streaks and to generate velocity vectors. The strategy used was to scan through a row of an image looking for a significant contrast between two near-adjacent horizontal pixels (dark to bright transition, Fig. 5). If the search was unsuccessful then the code jumped a few rows and repeated the same process. Eventually this process furnished a point on the left edge of the streak (point I, Fig. 5 ). The software then stepped across the streak looking for the right edge ( point 2, Fig. 5) of the streak based on a reverse transition (bright to dark). The software then calculated the center location of a strea~ :,:y taking the average of the right and left edge pixel values (point 3, Fig. 5). The algorithm then moved up a few pixels and repeated the same process, attempting to generate another point on the major axis of the same streak (points 4, 5 and 6, respectively, Fig. 5). If the search moving up was not successful due to the location and orientation of the streak (streak slopes to the left) then the software moved over to the right and then down to find the second point. After the two central points on a streak have been established (points 3 and 6, Fig. 5), the major axis of the streak was modeled as a straight line. The program then walks along this line in order to detect a transition between pixels at the end of the streak (bright to dark transitions, points 7 or 8, Fig. 5). When the location of one end of the streak has been determined, the program reverses direction and finds the other end of the streak. In this way, the ends of the streak were established. Finally, the length of a streak was converted to a velocity by dividing by the shutter duration. During the search, several independent tests were performed on the streak, if any of the tests for the predicted behavior failed then the streak was discarded. The independent tests that were performed on the streaks were that it must be straight, it must have a certain gray scale gradient with its near adjacent point (gray scale level between light to dark transition), it must not be too wide and it must not be too long. By adjusting filtering parameters it was found that outof-focus streaks could be identified and were rejected in favor of in-focus streaks.
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B.A. Saadevandi, R. Turton I Powder Technology 98 (1998) 183-189
In order to confirm the above strategy the reproducibility of the software measurements was tested at two different shutter speed ( 1 and 2 ms) to obtain a statistically significant estimate of the velocity at a given location and at the same conditions (Table 2). The results show that the mean velocities taken with a shutter speed of I ms are in good agreement, within a 95% confidence interval (CI), with those taken at a shutter speed of 2 ms, at the same conditions. Thus, the software predictions are statistically reproducible at different shutter speeds. Also the results predicted by the software were compared with those obtained using a high speed video system (Table 3). The high speed system was the Kodak Ekta Pro EM Motion Analyzer, model 1012, capable of recording up to 1000 full-frames/s. Comparisons of the velocity measurements taken by the software and the Kodak system, show that the mean velocity measurements for both systems were within the 95% confidence for all but two sets of experiments. In addition, the average absolute error between the means for all seven experiments was less than 6%. The high speed Kodak system was also used to confirm the positive movement of particles, notably at the wail, in the draft tube since the computer-based imaging system and software could not discriminate between positive (upward) and negative (downward) velocities. Hence, assuming that the mean velocity measurements with the Kodak system are the true particle velocities projected in two-dimensions in the draft tube, it may be concluded that the imaging software developed in this work gave similar results for particle velocities. It should be noted that previous work by He at al. I9] has shown the existence of a curtain effect at the front face of the semi-circular bed. This significantly changes the velocity pro-
file at the front of the bed. Therefore, data from a semi-circular bed may not reflect the profile in an equivalent circular bed operating at the same conditions. Nevertheless, the data from such a bed gives a valuable picture of both the voidage and velocity profiles in the draft tube and shows how these profiles change with fluidizing conditions, bed geometry, etc.
3. Experimental results Particle velocity and voidage profiles in the draft tube were obtained at different axial locations above the distributorplate and at two operating conditions. These conditions were at two levels of solids loading in the draft tube. These Ioadings correspond to low and high particle density flow conditions in the draft tube. These were obtained by adju,,ing the distance between the draft tube and the distributor plate (low and high particle density correspond to a distance of 5 and I 0 mm, respectively). The measurements were carried out at three particle diameters from the flat wall's surface and along the diameter of the draft tube. Previous investigation [ 9] has shown that particle velocities adjacent to the wall are lower than the peak values, obtained at approximately 2 to 3 mm away from the front wall surface. The solids flow and voidage patterns obtained at both sets of conditions were qualitatively similar. Some typical results are shown in Figs. 6 and 7 at high solids loading. In general, the particle velocity decreases with radial distance from the spout axis, except at z = 30 mm where the particle velocity increases with radial distance (Fig. 6). This is consistent with the observed particle movement at the bottom of the draft tube, whereby particles in the
Table 2 Comparison of the results obtained for particle velocityusing the video imagingsystemand software,at the same location and at the sameoperating conditions. using two different shutter speeds Measurement location axial distance from distributor plate = 20 mm
Sample size (N)
Average velocity + 95% CI (mm/s~
Shutter speed = 0.002 s Shutter speed = 0.001 s Shutter speed = 0.002 s Shutter speed= 0.001 s
100 100 1000 1000
498.7 + 29.3 504.0 + 31.2 483.0 4. I 1.0 501.9 :i: 10.6
Table 3 A comparison of the prediction of the particle velocity software and the high-speed Kodak system,at the same conditions Measurement location and solids loading (z in ram)
Particle velocitysoftware U..........pvs 4-95% Ci (mm/s)
20; low loading 50; low loading 50; low loading 50; high loading 50; high loading !50; low loading 150; low loading
547.6 + 35. I 961.2 + 31.3 909.2 4. 38.5 848.3 + 46. ! 868.0 4-33.8 !260.1 4-50.0 1002.1 4. 49.7
Kodak Ekta Pro system U.........Ks4-95~ C! (ram/s)
Relative error ( c~) t ( U,.m~,.pv.~-U.........,~Ks)X 1001/ ( U,.,,cjnPVS )
592.9 + 23.2 959.8 + 28.0 945.8 + 33.4 846.8 + 32. I 931.2 4-25.6 1207.3 ± 33.8 I 163.6! 29.4
- 8.27 0.14 - 4.03 0.18 - 7.28 4.19 - 16.12
B.A. Saadevandi, R. TurtonI Powder ; echnology 98 (1998) 183-189
188
Ilia
~____~_7~1~__n~
e - z - 90mm
Table 4 " ~" A comparison of the solids mass flowrates in the draft tube at different axial locations and at different solids Ioadings
-O-z- 30 mm _J
14m: tIM:
./
'"
i!I"
z (in ram)
i .t.@_.~.A ~
I
Solids mass flow rate (kg/s)
'
me
-
z- l
IIM 0 40
~
4o
40
.t0
o
t0
ao
30
4o
ao
r Imm) Fig. 6. Axialcomponentof particlevelocityprofilein the draft tube (data points are time-averagedvalues of spatially-averagedvelocitiesover the fieldof view), Itmllal O i l l n ~ ,
30 60 90 120 150 200
,,
r
/
i
'-~,
',
Left quadrant
Right quadrant
Left quadrant
Right quadrant
0.0253 0.0257 0.0237 0.0239 0.0222 0.0231
0.0241 0.0212 0.02 ! 3 0.0240 0.0232 0.0227
0.0679 0.0632 0.0618 0.0626 0.0650 0.0708
0.0704 0.0566 0.0600 0.0625 0.066 ! 0.0713
rd
ms = Trppf Ut( l-e~)rdr o
-I ",,I
High solids loading
rate of solids was computed using the radial particle velocity and voidage profiles from Eq. ( I ).
"~ o~'lLB_~mA~m.~i.~~' 4~ Z mlr~'lg_mm..._~_~-~~ m ~ O ~ l : 1
P )o ! . - 4 - ,
Low solids loading
I
O.II?O~ l l d i l l Oiltance, r Imml Fig. 7. Voidage profile in the draft tube (data points are lime-averaged values of spatially-averaged voidages in a volume equal to the lield of view multiplied by the depth of lield).
dense, downward moving annular bed reverse direction and flow through the gap between the distributor plate and the bottom of the draft tube, Overall, particles flow radially inward andas they art exposed to the high upward air velocity they start to accelerate and flow upward in the draft tubt: Therefore, this flow pattern establishes a region of low solid density and velocity at the center and bottom of the draft tube. Likewise, the voidage increases with radial distance from the spout axis, except at z = 30 mm level where the voidage decreases with radial distance. Clearly, the region at the intersection of the curved draft tube wall and the flat front face is influenced significantly by the semi-circular geometry. However, the above results are consistent both with visual observations and th¢ explanations given above. Close to the base of the draft tube and closer to the wall the voidage is low indicating a dense particle region. As particles move into the draft tube and art accelerated in the vertical direction the voidage increases. As an independent test of consistency for the particle velocity and voidag¢ data an overall solids mass balance was performed. Based on a steady state condition, the upward solids mass flow rate at any cross-section in the draft tube must be equal for the same operating conditions. Thus, the mass flow
( I)
The mass flow rates of solids were evaluated at different axial locations from the distributor plate and were shown to be within + 10% of the average values (Table 4).
4. Conclusions
The results of this work indicate that non-invasive computer-based video imaging techniques using customized software can be applied successfully to the measurement of particle velocity and voidage profiles in the draft tube region of a semi-circular spouted bed. Overall, the particle velocity decreases and voidage increases with radial distance from the center of the draft tube and with increasing distance from the distributor at both loading conditions, except at the bottom of the bed (z = 30 ram), where the particle velocity increases and voidage decreases with radial distance. The reason for this behavior is due to inward and upward motion of particles at the bottom of the draft tube, establishing a region of low solids density and velocity at the center and bottom of the draft tube. Future work is focused on the investigation of the solids flow pattern at higher loadings, and with larger non-spherical particles, consistent with industrial practice.
5. N o m e n c l a t u r e
dp m., N r ro
Particle diameter (m) Solids mass flowrate (kg/s) Sample size Radial coordinate (m) Draft tube radius (m)
B.A. Saadevandi, R. Turton/ Powder Technology 98 (1998) io.,-,~. ,o~ I ~ o
U, U: U~ x z
Radial component of particle velocity (m/s) Axial component of particle velocity (m/s) 2-D particle velocity in the draft tube (m/s) Coordinate perpendicular to the front face of the bed (m) Axial coordinate measured from the distributor plate (m)
Greek letters ~ pp
Voidage in the draft tube Solid particle density ( kg/m 3)
specifics of the computer-based video imaging techniques at the early stage of this work and Kodak for the use of the Ekta Pro EM Motion Analyzer.
References [I] 12l [ 3] [41 [5] [6]
Subscripts KS Kodak system mean Average PVS Particle velocity software
[ 71 J SI [9 ] I I01 IIII
Acknowledgements The authors would like to acknowledge the DOE EPSCOR program for supporting this work. The authors would also like to acknowledge Umbrella Inc. for their consulting on the
189
112]
X.X. Cheng, R. Turton, AIChE Symp. Ser. 90 (301) (1994) 142. N.P. Cheremisinoff, Ind. Eng. Chem. Process Dev. 25 (1986) 329. K.B. Mathur, P.E. Gishler, AIChE J. I (1955) 157. L. Massimilla, J.W. Westwater, AIChE J. 6 (1959) 132. G.C. Suciu, M. Patrascu, Powder Tech. 19 (1978) 109. D.V. Van Velzen, H.J. Flamm, H. Langenkamp, A. Casile, Can. J. Chem. Eng. 52 (1974) 156. M.I. Boules, B. Waldie, Can. J. Chem. Eng. 64 (1986) 939. D. Roy, F. Larachi, R. Legros, J. Chaouki, Can. J. Chem. Eng. 72 (1994) 945. Y.L. He, S.Z. Qin, C.J. Lira, J.R. Grace, Can. J. Chem. Eng. 72 ( ! 994 ) 561. G.A. Lefroy, J.F. Davidson, Trans. inst. Chem. Eng. 47 ( ! 969) T120. Y.L. He, C.J. Lira, J.R. Grace, J.X. Zhu, S.Z. Qin, Can. J. Chem. Eng. 72 (1994) 229. B.A. Saadevandi, The use of imaging techniques to study the hydrodynamics of particle motion in a fluidized bed coating device in the region of liquid spray, PhD Dissertation, West Virginia University, Morgantown, WV, 1996.
Powder Technology 98 ( 1998 ) 183-189
The application of computer-based imaging to the measurements of particle velocity and voidage profiles in a fluidized bed Bram A. Saadevandi i, Richard Turton * Deportment t!f Chemh'al Engineering, West Virginia University, P.O. Box 6102, Morgantown, WV 26506-6102. USA Received 9 March 1998
Abstract Computer-based video imaging techniques were utilized in order to measure the axial and radial components of particle velocity and voidage profiles in the draft tube region of a semi-circular spouted fluid bed coating device. Computer images were obtained using standard RS- 170 video signals ( 30 frames/s) from an image processing board and a CCD variable shutter speed camera. When measuring particle velocities. low shutter speeds of I-2 ms were utilized. Due to rapid motion of particles, the images obtained were blurred streaks several millimeters in length. The length and direction of streaks were proportional to the magnitude and direction of the projected velocity vector. By using dispersed back lighting, the particle velocity images appeared as light streaks on a dark background. Custom software was written in order to automatically search for and to identify bright streaks and calculate particle velocities. The velocity measurements obtained from the software were compared with data taken with a high speed Kodak video system ( 1000 frames/s with a 20-p,s strobe). The results were in close agreement. The video images for analysis of voidage measurements were obtained using the same techniques as for the velocity measurements except with a shutter speed of 0. i ms. The images thus obtained showed the particles to have a dark outer ring with a light center. The search algorithm for identifying particles involved establishing the gray level for nine different locations: eight compass points and a center point. By searching the frame for the presence of particles, and then comparing the gray levels at the circumference and the center of the particle image it was possible to distinguish between in-tbcus and out-of-focus particles. A comparison of the results using the software with those of standard models made with glass beads, and by visually counting the particles, was in close agreement. © 1998 Elsevier Science S.A. All rights reserved. Keywords: Computer-based imaging: Particle velocity; Voidage proliles: Fluidi,,.ed bed: Axial component: Radial component
I. Introduction Studies of the hydrodynamics of fluid bed coating devices are essential in order to predict and scale-up the performance of commercial-scale units from results obtained in smallscale laboratory equipment. Investigations by Cheng and Turton [ I ], on the uniformity of particle coating in a draft tube spouted bed of I mm diameter particles, have shown that the hydrodynamics in the spray zone is the dominant factor affecting the unilbrmity of particle coating. Information on particle velocity and voidage profiles in the spout and annular regions as well as in the spray zone of these beds is vital to the understanding and prediction of bed perlbrmance. There have been numerous methods of measuring the velocity of particles and voidage in gas-solid fluid systems. * Corresponding author. Tel.: + 1-304-293-211 ! ext. 415: Fax: + 1-304293-4139; E-mail: [email protected] Present address: General Electric, GE Plastics. P.O. Box 68, Washington, WV 26181. USA. 0032-5910/98/$19.00 © 1998 Elsevier Science S.A. All rights reserved. Pll S 0 0 3 2 - 5 9 ! 0 ( 98 ) 0 0 0 5 6 - 4
A review of these methods is given by Cheremisinoff 121. Cinephotography has been one of the major techniques used for studying the hydrodynamics of particles in a ftuidized bed. However, photography is a very time consuming technique, even with a digitizer to aid analyzing panicle coordinate data. Framing frequencies of 2000-3000 Hz were utilized by several investigators to measure particle velocity in the spout region 13-51. Other techniques such as radioactive tracer, laser Doppler anemometry, 7-ray emission and fiber optic probes have been used to measure panicle velocities in a spouted bed 16-91. Some of the techniques, which were mentioned above, have also been employed to measure voidage in fluidized beds. Lefroy and Davidson 1101 employed a direct photographic technique to measure the voidage profile in a spouted bed column. This technique consisted of photographing the spout, in a semi-circuhn column. and comparing the number of particles per unit area with a number in a similar area of the packed bed annulus, for which the voidage was known. He et al. ! II I recently used a fiber
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optic probe to measure voidage profile in a full and half spouted fluid beds. This paper describes the application of computer-based video imaging, to measure particle velocity and voidage profiles in a spouted fluid bed coating device. This technique is non-intrusive and is shown to be capable of providing reliable particle velocity and voidage profiles in the spout.
2. Experimental equipment and procedure The experimental equipment used in this research is shown schematically in Fig. ~ The apparatus consisted of a semicircular spouted bed with a draft tube insert. The bed was 22,9 cm (9 in.) in diameter and 59.7 cm ( 23.5 in.) high and the draft tube insert was 10.2 cm (4 in.) in diameter and 35.6 cm ( 14 in.) high. The bottom of the draft t~lbe was angled at 60 ° from horizontal as shown in Fig. I, insert A. This moditication reduced the flow of particles towards the spray nozzle and assisted the particle flow pattern upward through the spray zone. The draft tube was pressed onto the fiat front lace of the bed using spring-loaded bolts located at the back of the bed. This design allowed the draft tube to be adjusted easily up or down relative to the distributor plate. The major portion of the bed was made from transparent Plexiglas with a transparent glass front face, 6.35 mm thick. The whole assembly was bolted to a metal frame. The distributor plate consisted of a 316L stainless steel sintered plate, 2.4 mm thick with 100/.tm pores, which separated the bed from a split plenum. In order to operate with maximum flexibility the lower portion of the bed ( plenum chamber) was split into an inner and outer section with independent air supplies to each region. The fluidizing air was supplied by two centrifugal blowers in series and regulated through rotameters prior to entering the central and annular regions of the bed. Finally, the bed was equipped with a semi-circular spray nozzle located at the center of the distributor plate and at the Ih)nt face of the equipment, The spray nozzle was an air atomizing type with an air cap in which a coating liquid was sprayed into the bed Top Views
......
Veal to Atmosphere Front View 4
no,-,et a'i"o"P"Y
Side View
using compressed air as the atomizing fluid. For this work the air cap was cut in half and adapted to fit the spray nozzle so as to provide an 180° spray pattern using three orifices. Water was used as a model spray liquid and spray conditions were chosen so as to avoid any agglomeration of particles during the experiments. The whole equipment was essentially a typical small scale fluid bed coating apparatus cut in half. The basic experimental principle in this work was to acquire computer images using a standard RS- 170 video signal (30 frames/s) from an image processing board and a camera. In this study the movement of closely sized glass beads (dp= i.086 mm and po = 2500 kg/m 3) was observed through the front face of the semi-circular fluid bed using a charged couple device (CCD) variable shutter speed camera ( Pulnix TM-7CN equipped with a C-mount 50 mm Fuji lens with aperture f/I.4 attached to a 20-ram extension tube). Customized software was developed una automated to interpret the computer-based digitized images through an image processing board ( Data Translation's DT-385 I- I with display resolution of 640 × 480) and used to measure particle velocity and voidage proliles at the front face of the fluidized bed. When tracking an object using an RS-170 video signal, a problem arises during frame grabbing that is known as interline blurring. A frame consist of two fields (even and odd lieids) which are taken 16.7 ms (60 ~ ~ s) apart. Thus two consecutive fields are spliced together to form a single frame. Since the intbrn~ation in a frame is made up I'rom images that are 16.7 ms apart, the resulting inlormation is smeared. To alleviate this problem, the even and odd lields of a single frame are split apart prior to analyzing pixel data. By splitting the frames one obtains a clearer, sharper image, although the vertical resolution per field is reduced by a factor of two, while the horizontal resolution is unafl'ected. In this work, only the even lields were analyzed. in the current work, the framing rate is not of great importance since, as will be shown later, both voidage and velocity data are obtained from a single lield. However, it is also possible to analyze the odd lields and this would allow video measurements to be obtained at an effective framing rate of 60 Hz. if particle-tracking algorithms were to be implemented, then the use of a higher effective framing rate would be of importance. Finally, the hghting arrangement is also a very important aspect of this technique, and must be optimized with respect to the equipment geometry and particle loading in the bed.
Monitor
2. I. Calibration tecimique fiJr depth o.lifield
~
IC~lial~ Solution
.
•
"L I'l~l ~
FrameGrabber
-~
Fig. I. Schematic diagram of fluidized bed and video imaging system.
In order to t~valuate wall effects, which arise from the gaswall and particle-wall interactions, the particle velocity and voidage measurements were carried out at the front wall and at a distance in from the wall's surface. Hence, it was necessary to develop a calibration technique to determine precisely the field of view and depth of field of the optical system and the exact location of the measurements during the exper-
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B.A. Saadevandi, R. Turton / Powder Technology 98 (1998) 183-189
Thin Transparent Thread
Thin Acrylic Sheet (0.$ mm thick)
N y l o n ~I.I.I.I.I,I,N
Spotlights
White Screen
(300 art e a e h ) ~ T i Fluidized Bed ~ (Top View)
I00 cm 50 c
Camera
Fig. 3. Dispersed back lighting arrangements. Glass Partic es
(!.086 mm diameter) Fig. 2. Diagramof standard sample for testing depth of field of camera and standard sample set-up in fluidizedbed.
iments. For this purpose, standard samples were constructed from the same glass particles used in the experimental work, Fig. 2. Glass particles were glued to the surface of several layers of thin transparent acrylic sheets (thickness=0.5 mm), and placed inside the dral't tube of :t second identical semi-circular bed (same dimensions as the original bed) against the fiat wall's surface. Additional particles were attached to several thin rods positioned vertically in the background (inside the draft tube) so as to simulate the lighting conditions in the actual bed, see Fig. 2. During an experimental run, a portion of the dispersed back lighting will be adsorbed by the particles in the background due to the dynamic environment. By placing the rods in the background during the calibration experiments, it was possible to simulate the lighting conditions occurring when the actual bed is running. The depth of field was determined by tbcusing on the first layer of particles of a standard sample ( Fig. 2) located at the wall, and moving to each successive layer of particles until the previous layer became slightly out of locus. In addition, each layer's peak Ibcusing point was precisely marked on the lens lbr proper depth calibration from the wall's surface. Using these techniques, the depth of field of the camera was measured to be 5.0 mm, details of the field of view calibration and the pixel-length conversion lbr particle velocity and voidage are given elsewhere I 121.
2.2. Voidage proJile measurements hi the dra/'t tube in order to estimate the radial and axial voidage profiles, the camera was tbcused on an I cm by I cm area in the draft tube. The camera was focused approximately 3 mm inside the glass front lace of the bed. A fast shutter speed of 0. ! ms was utilized to capture clear images of particles in the draft tube. This analysis of voidage was for a 1 cm by i cm by 0.5 cm volume region. The voidage measurements were obtained by taking a series of images of the bed. Customized software was written to automatically identify and count the number of particles in a given volume equal to the field of view multiplied by the depth of field of the optical system. As was explained earlier, in order to eliminate the interline blurring once a frame of video was acquired, the even field
Particle ImagesObtained using Dispersed Back Lighting (bright center and dark annular ring)
O:
IoOOo 8 Compass Points and Center Point Location for Particle Search Algorithm
Fig. 4. Diagramshowingtypicalfieldobtainedduringvoidagemeasurements and the location of test pixels used in particle identification.
was stripped numerically from it. The main function of the software was to count the number of particles that met all the test criteria within a region of interest in a field. This was established with a main loop that counted down through each row of video data. Within each iteration of the main loop a secondary loop was used to step through a row looking for every third pixel in that row. By utilizing the dispersed back lighting arrangement (Fig. 3) the images of the particles showed a dark outer ring with a bright center (Fig. 4). Thus at every third pixei in a field the software established an analysis of the brightness value of nine pixels. These pixels included eight equally spaced points around the circumference and a point at the center of the pattern. The distance of the center point from the compass points was determined based on the average radius of the glass particles convened to the appropriate number of pixels. Once the nine points were established, two test were applied by the software in order to determine whether a point is at the center of the particle. First, the software counted how many of the eight pixels fell below a given gray scale (0 to 255, black to white) value. If six or more points qualified, then the software proceeded to the next test. Second, the software counted how many of the eight pixels had more than a certain threshold difference with the center pixel. If six or more points did, then panicle was determined to be in focus. In essence, only in-focus particles were counted in the determination of the voidage. In order to confirm the above strategy, standard samples with known voidage were made from glass beads (the samples which were described in Section 2. I for calibration tech-
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Table ! Comparison of results obtained for voidage at the same location and at the same operating conditions using the video imaging system and software Sample size (N)
Average voidage + 95% CI
100 100 100 ! 00
0.897 + 0.007 0.899 4- 0.006 0.895 4- 0.007 0.893 4- 0.007
niques, see Fig. 2). The standard samples were placed inside the draft tube of a second identical semi-circular bed against the front wall surface (Fig. 2). Using standard samples with known voidage, within the given depth of field, 5 mm, and the dispersed back lighting arrangement, known voidage values for each sample and the voidage given by the software were compared. There was close agreement between the measured voidage by the software and the known voidage calculated for each sample. The idea here was to demonstrate that the voidage values given by the software were correct, and corresponded to the number of in-focus particles within the depth of field of the camera. In addition, the reproducibility of measurements taken by the imaging software, at a particular location and at the same conditions was investigated. A comparison of the mean voidage calculated by the software for replicated experiments at the same conditions showed that the mean voidage values were in good agreement with each other, as shown in Table I. Therefore, repeated measurements at different solids Ioadings were used to obtain statistically significant estimates of the voidage at a given location and set of operating conditions. Due to the ability of the software to discriminate in-focus and out-of-locus particles, the particle count within the field of view is a direct measurement of the voidage within a bed volume of I cm × I cm X 0.5 cm (field of view x depth of field).
2.3, Particle velocity prt!/ile measurements in the drt!/'t robe Particle tracking software was developed and automated to carry out the radial particle velocity profiles at different axial locations above the distributor plate in the draft tube region of the bed. A similar technique as described above for voidage profiles was utilized to measure particle velocities. Shutter speeds of I to 2 ms were determined to be the most appropriate for the range of particle velocities in the draft tube. By reducing the shutter speed and by utilizing dispersed back lighting, Fig. 3, images were produced that were bright streaks on a dark background ( Fig. 5). The lengths of streaks, typically several millimeters, are directly proportional to the local speed of the particle. Also the direction of a streak is an accurate measurement of a particle's velocity (U,) in twodimensions (U, and U=). Customized software was written to automatically identify a particle streak and to measure the length and direction of the particles" movement. As in the case of the voidage measurements, only even fields of frames were analyzed. The even fields were searched
Location of Dark-Bright Transitions used to Identify Particle Streaks
/ Particle Traces using Slow Shutter Speed (bright streaks on a dark background) Fig. 5. Diagram showing typical field obtained during velocity measurements, the location of test pixels used in streak identilication and the coordinate system adopted.
in order to identify qualified bright streaks and to generate velocity vectors. The strategy used was to scan through a row of an image looking for a significant contrast between two near-adjacent horizontal pixels (dark to bright transition, Fig. 5). If the search was unsuccessful then the code jumped a few rows and repeated the same process. Eventually this process furnished a point on the left edge of the streak (point I, Fig. 5 ). The software then stepped across the streak looking for the right edge ( point 2, Fig. 5) of the streak based on a reverse transition (bright to dark). The software then calculated the center location of a strea~ :,:y taking the average of the right and left edge pixel values (point 3, Fig. 5). The algorithm then moved up a few pixels and repeated the same process, attempting to generate another point on the major axis of the same streak (points 4, 5 and 6, respectively, Fig. 5). If the search moving up was not successful due to the location and orientation of the streak (streak slopes to the left) then the software moved over to the right and then down to find the second point. After the two central points on a streak have been established (points 3 and 6, Fig. 5), the major axis of the streak was modeled as a straight line. The program then walks along this line in order to detect a transition between pixels at the end of the streak (bright to dark transitions, points 7 or 8, Fig. 5). When the location of one end of the streak has been determined, the program reverses direction and finds the other end of the streak. In this way, the ends of the streak were established. Finally, the length of a streak was converted to a velocity by dividing by the shutter duration. During the search, several independent tests were performed on the streak, if any of the tests for the predicted behavior failed then the streak was discarded. The independent tests that were performed on the streaks were that it must be straight, it must have a certain gray scale gradient with its near adjacent point (gray scale level between light to dark transition), it must not be too wide and it must not be too long. By adjusting filtering parameters it was found that outof-focus streaks could be identified and were rejected in favor of in-focus streaks.
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B.A. Saadevandi, R. Turton I Powder Technology 98 (1998) 183-189
In order to confirm the above strategy the reproducibility of the software measurements was tested at two different shutter speed ( 1 and 2 ms) to obtain a statistically significant estimate of the velocity at a given location and at the same conditions (Table 2). The results show that the mean velocities taken with a shutter speed of I ms are in good agreement, within a 95% confidence interval (CI), with those taken at a shutter speed of 2 ms, at the same conditions. Thus, the software predictions are statistically reproducible at different shutter speeds. Also the results predicted by the software were compared with those obtained using a high speed video system (Table 3). The high speed system was the Kodak Ekta Pro EM Motion Analyzer, model 1012, capable of recording up to 1000 full-frames/s. Comparisons of the velocity measurements taken by the software and the Kodak system, show that the mean velocity measurements for both systems were within the 95% confidence for all but two sets of experiments. In addition, the average absolute error between the means for all seven experiments was less than 6%. The high speed Kodak system was also used to confirm the positive movement of particles, notably at the wail, in the draft tube since the computer-based imaging system and software could not discriminate between positive (upward) and negative (downward) velocities. Hence, assuming that the mean velocity measurements with the Kodak system are the true particle velocities projected in two-dimensions in the draft tube, it may be concluded that the imaging software developed in this work gave similar results for particle velocities. It should be noted that previous work by He at al. I9] has shown the existence of a curtain effect at the front face of the semi-circular bed. This significantly changes the velocity pro-
file at the front of the bed. Therefore, data from a semi-circular bed may not reflect the profile in an equivalent circular bed operating at the same conditions. Nevertheless, the data from such a bed gives a valuable picture of both the voidage and velocity profiles in the draft tube and shows how these profiles change with fluidizing conditions, bed geometry, etc.
3. Experimental results Particle velocity and voidage profiles in the draft tube were obtained at different axial locations above the distributorplate and at two operating conditions. These conditions were at two levels of solids loading in the draft tube. These Ioadings correspond to low and high particle density flow conditions in the draft tube. These were obtained by adju,,ing the distance between the draft tube and the distributor plate (low and high particle density correspond to a distance of 5 and I 0 mm, respectively). The measurements were carried out at three particle diameters from the flat wall's surface and along the diameter of the draft tube. Previous investigation [ 9] has shown that particle velocities adjacent to the wall are lower than the peak values, obtained at approximately 2 to 3 mm away from the front wall surface. The solids flow and voidage patterns obtained at both sets of conditions were qualitatively similar. Some typical results are shown in Figs. 6 and 7 at high solids loading. In general, the particle velocity decreases with radial distance from the spout axis, except at z = 30 mm where the particle velocity increases with radial distance (Fig. 6). This is consistent with the observed particle movement at the bottom of the draft tube, whereby particles in the
Table 2 Comparison of the results obtained for particle velocityusing the video imagingsystemand software,at the same location and at the sameoperating conditions. using two different shutter speeds Measurement location axial distance from distributor plate = 20 mm
Sample size (N)
Average velocity + 95% CI (mm/s~
Shutter speed = 0.002 s Shutter speed = 0.001 s Shutter speed = 0.002 s Shutter speed= 0.001 s
100 100 1000 1000
498.7 + 29.3 504.0 + 31.2 483.0 4. I 1.0 501.9 :i: 10.6
Table 3 A comparison of the prediction of the particle velocity software and the high-speed Kodak system,at the same conditions Measurement location and solids loading (z in ram)
Particle velocitysoftware U..........pvs 4-95% Ci (mm/s)
20; low loading 50; low loading 50; low loading 50; high loading 50; high loading !50; low loading 150; low loading
547.6 + 35. I 961.2 + 31.3 909.2 4. 38.5 848.3 + 46. ! 868.0 4-33.8 !260.1 4-50.0 1002.1 4. 49.7
Kodak Ekta Pro system U.........Ks4-95~ C! (ram/s)
Relative error ( c~) t ( U,.m~,.pv.~-U.........,~Ks)X 1001/ ( U,.,,cjnPVS )
592.9 + 23.2 959.8 + 28.0 945.8 + 33.4 846.8 + 32. I 931.2 4-25.6 1207.3 ± 33.8 I 163.6! 29.4
- 8.27 0.14 - 4.03 0.18 - 7.28 4.19 - 16.12
B.A. Saadevandi, R. TurtonI Powder ; echnology 98 (1998) 183-189
188
Ilia
~____~_7~1~__n~
e - z - 90mm
Table 4 " ~" A comparison of the solids mass flowrates in the draft tube at different axial locations and at different solids Ioadings
-O-z- 30 mm _J
14m: tIM:
./
'"
i!I"
z (in ram)
i .t.@_.~.A ~
I
Solids mass flow rate (kg/s)
'
me
-
z- l
IIM 0 40
~
4o
40
.t0
o
t0
ao
30
4o
ao
r Imm) Fig. 6. Axialcomponentof particlevelocityprofilein the draft tube (data points are time-averagedvalues of spatially-averagedvelocitiesover the fieldof view), Itmllal O i l l n ~ ,
30 60 90 120 150 200
,,
r
/
i
'-~,
',
Left quadrant
Right quadrant
Left quadrant
Right quadrant
0.0253 0.0257 0.0237 0.0239 0.0222 0.0231
0.0241 0.0212 0.02 ! 3 0.0240 0.0232 0.0227
0.0679 0.0632 0.0618 0.0626 0.0650 0.0708
0.0704 0.0566 0.0600 0.0625 0.066 ! 0.0713
rd
ms = Trppf Ut( l-e~)rdr o
-I ",,I
High solids loading
rate of solids was computed using the radial particle velocity and voidage profiles from Eq. ( I ).
"~ o~'lLB_~mA~m.~i.~~' 4~ Z mlr~'lg_mm..._~_~-~~ m ~ O ~ l : 1
P )o ! . - 4 - ,
Low solids loading
I
O.II?O~ l l d i l l Oiltance, r Imml Fig. 7. Voidage profile in the draft tube (data points are lime-averaged values of spatially-averaged voidages in a volume equal to the lield of view multiplied by the depth of lield).
dense, downward moving annular bed reverse direction and flow through the gap between the distributor plate and the bottom of the draft tube, Overall, particles flow radially inward andas they art exposed to the high upward air velocity they start to accelerate and flow upward in the draft tubt: Therefore, this flow pattern establishes a region of low solid density and velocity at the center and bottom of the draft tube. Likewise, the voidage increases with radial distance from the spout axis, except at z = 30 mm level where the voidage decreases with radial distance. Clearly, the region at the intersection of the curved draft tube wall and the flat front face is influenced significantly by the semi-circular geometry. However, the above results are consistent both with visual observations and th¢ explanations given above. Close to the base of the draft tube and closer to the wall the voidage is low indicating a dense particle region. As particles move into the draft tube and art accelerated in the vertical direction the voidage increases. As an independent test of consistency for the particle velocity and voidag¢ data an overall solids mass balance was performed. Based on a steady state condition, the upward solids mass flow rate at any cross-section in the draft tube must be equal for the same operating conditions. Thus, the mass flow
( I)
The mass flow rates of solids were evaluated at different axial locations from the distributor plate and were shown to be within + 10% of the average values (Table 4).
4. Conclusions
The results of this work indicate that non-invasive computer-based video imaging techniques using customized software can be applied successfully to the measurement of particle velocity and voidage profiles in the draft tube region of a semi-circular spouted bed. Overall, the particle velocity decreases and voidage increases with radial distance from the center of the draft tube and with increasing distance from the distributor at both loading conditions, except at the bottom of the bed (z = 30 ram), where the particle velocity increases and voidage decreases with radial distance. The reason for this behavior is due to inward and upward motion of particles at the bottom of the draft tube, establishing a region of low solids density and velocity at the center and bottom of the draft tube. Future work is focused on the investigation of the solids flow pattern at higher loadings, and with larger non-spherical particles, consistent with industrial practice.
5. N o m e n c l a t u r e
dp m., N r ro
Particle diameter (m) Solids mass flowrate (kg/s) Sample size Radial coordinate (m) Draft tube radius (m)
B.A. Saadevandi, R. Turton/ Powder Technology 98 (1998) io.,-,~. ,o~ I ~ o
U, U: U~ x z
Radial component of particle velocity (m/s) Axial component of particle velocity (m/s) 2-D particle velocity in the draft tube (m/s) Coordinate perpendicular to the front face of the bed (m) Axial coordinate measured from the distributor plate (m)
Greek letters ~ pp
Voidage in the draft tube Solid particle density ( kg/m 3)
specifics of the computer-based video imaging techniques at the early stage of this work and Kodak for the use of the Ekta Pro EM Motion Analyzer.
References [I] 12l [ 3] [41 [5] [6]
Subscripts KS Kodak system mean Average PVS Particle velocity software
[ 71 J SI [9 ] I I01 IIII
Acknowledgements The authors would like to acknowledge the DOE EPSCOR program for supporting this work. The authors would also like to acknowledge Umbrella Inc. for their consulting on the
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112]
X.X. Cheng, R. Turton, AIChE Symp. Ser. 90 (301) (1994) 142. N.P. Cheremisinoff, Ind. Eng. Chem. Process Dev. 25 (1986) 329. K.B. Mathur, P.E. Gishler, AIChE J. I (1955) 157. L. Massimilla, J.W. Westwater, AIChE J. 6 (1959) 132. G.C. Suciu, M. Patrascu, Powder Tech. 19 (1978) 109. D.V. Van Velzen, H.J. Flamm, H. Langenkamp, A. Casile, Can. J. Chem. Eng. 52 (1974) 156. M.I. Boules, B. Waldie, Can. J. Chem. Eng. 64 (1986) 939. D. Roy, F. Larachi, R. Legros, J. Chaouki, Can. J. Chem. Eng. 72 (1994) 945. Y.L. He, S.Z. Qin, C.J. Lira, J.R. Grace, Can. J. Chem. Eng. 72 ( ! 994 ) 561. G.A. Lefroy, J.F. Davidson, Trans. inst. Chem. Eng. 47 ( ! 969) T120. Y.L. He, C.J. Lira, J.R. Grace, J.X. Zhu, S.Z. Qin, Can. J. Chem. Eng. 72 (1994) 229. B.A. Saadevandi, The use of imaging techniques to study the hydrodynamics of particle motion in a fluidized bed coating device in the region of liquid spray, PhD Dissertation, West Virginia University, Morgantown, WV, 1996.