An investigation of panicle dynamics in a dilute phase pneumatic conveying system 

61). I lowever, the peak of each profile estimated by the numerical data is much closer to the pipe 

inner wall (the negative x direclion) than that in the experimental data. For U a y profiles on the x 

axis, both the experimental and numerical data display a similar decreasing tendency of U a y from 

the pipe outer wall to the pipe inner wall (along the negative x direction) at each section. The Ua y . 

profiles are much flatter, which is shown by the narrowed difference of U a y among the different 

points on the x axis. However, the numerical profile of U a y has a wider flat top region than the 

experimental profile of U a y does at the section OD and 2D, for the experimental cross-sectional 

distributions of U a y with the fastest velocity in Figure 4.5 are thinner than those ofthe numerical 

results in Figure 4.6. 

Figure 4.10 shows the experimental and numerical profiles o f U r a and U a y in the z axis. The 

symmetrical feature along the z axis is shown in both the experimental and the numerical profiles 

of Uax and U a y at each section. The profile peak of and the bottom of U a y are located at the 

point z=0. Another observed agreement for U a x or U a y is the similar profile shape between the 

experimental and the numerical profiles downstream of the section OD, In general, U M is faster in 

the pipe centre than in the pipe left (the z negative axis) and right sides (the z positive axis). By 

contrast, U a y is faster in the pipe two sides than in the pipe centre along the z axis. However, the 

profile shape of U a x and U a y has much discrepancy on the section OD, although their 

experimental and numerical profiles show a similar variation tendency. At the section OD, the 

experimental profile of U a x show a sharp peak at the point z=0, where the numerical profile of 

U a x shows a flat top. An d the numerical profile of U a y is very flat with a minor drop from the 

pipe two sides to the pipe centre along the z axis. In contrast, the experimental profile of U a y 

shows a deep minimum in the centre region around z=0 where U a y is slowest in the z axis. 

Comparing the one-dimensional profiles in Figure 4.9 and Figure 4.10 with the two-dimensional 

cross-sections distribution in Figure 4.5~4.8, we can see that the discrepancies between the 

experimental and numerical profiles of U a x and U a y in the x axis and the z axis at the section OD 

are mainly caused by the fact that the numerical positions ofth e highest velocity region of U „ 

and the horseshoe centre of U a y differ from the corresponding positions measured by experiments. 

65 

VES017100 
Chapter -1 l-.\pcrimcnlal studies of cross-sectional characteristics of air velocity in pipes 

U /<U > profiles On the z axis U /l i profiles On the zaxis 

6D 6D 

3TM | 

5 

0.8 

4D 

0.6 

1.2 

4D 

x

* °i 

2D 

0.6 

1.2 

2D 

3 

0 

OD 

0.6 

1.2 

OD 

C F D 

L D A 

-1 -0.6 -0.2 0.2 0.f 

Z/R 

0.8 

: CF O 

^ LD A 

-1 -0.6 -0.2 0.2 0.6 1 

z/R 

Figure 4.I0 Profiles of U „ and U a ) . along the z axis at four selected vertical cross-sections 

(

< U a x > is the mean absolute value of U„ ; U , is the air conveying velocity lOm/s) 

4.3 CONCLUSIONS 

The two calculated transform matrices, for the horizontal and vertical pipe flow measurements 

respectively, were used to arrange the shifting coordinates of the traverse system which carried 

the LD A probes to access measurement cross-sections in the horizontal pipe and the vertical pipe 

behind a horizontal-vertical 90° bend (R/D=l .3). 

On the two horizontal cross-sections, the experimental data of the axial air velocity (Ua x ) reveal 

an annular nature. Both the profiles of U u x on the y axis and the z axis agree with the empirical 

one-seventh power-law profile. On the eight vertical cross-sections from 0D to 7D, the 

66 

VES017101 
An investigation of particle dynamics in a dilute phase pneumatic conveying system 

horseshoe-like feature is displayed on each cross-sectional distribution of the axial air velocity 

( U a y ). Uay, is slower inside the horseshoe close to the pipe inner wall and U a y is faster in the 

region around the pipe outer wall. The difference of U a y between inside and outside of the 

horseshoe gradually decreases at further downstream sections from OD. A secondary flow is 

revealed in the cross-sectional distributions of the radial air velocity (U a x ), especially on the 

section OD. This secondary flow includes two circulations symmetrical along the z axis. Hence, a 

vertical cross-section can be classified into three regions of the mid strip and the two sectors 

outside the strip, according to Uax directions. On each section, the secondary flow on the mid 

strip is divided into two at the pipe outer wall. One subflow is accelerated towards the pipe inner 

wall along the pipe left wall and the other along the pipe right wall. Then two subflows are mixed 

at the region close to the pipe inner wall. The direction of the mixed flow is changed towards the 

pipe centre (in the positive x direction). Before reaching the pipe centre, the mixed flow is 

accelerated to obtain its maximum magnitude of U a x in the positive x direction. Then U K is 

decelerated to approach zero at the pipe outer wall. Thus, the left subflow with the mixed flow 

forms the circulation in the counter-clockwise direction. The right subflow with the mixed flow 

forms another circulation in the clockwise direction. However, at the further downstream sections 

of 4D to 6D, the secondary flow becomes weak, for the magnitude of Uax gradually decrease and 

the difference of Uax between the mid strip and its two sides is narrowed. 

A comparison of the experimental data by LD A and the numerical results by CFD indicate that 

both of them on the x axis and the z axis show a similar shape for the axial air velocity (U a y ) and 

the horizontal air velocity (Uax). 

67 

VES017102 
Chapter 5 

Experimental investigation of Particle Dynamics 

in a Dilute Pneumatic Conveying System using 

the Extended LDA Technique 

This chapter presents experimental results obtained by using the extended LDA technique introduced 

In Chapter 3, for the quantitative assessment of particle dynamic behaviour in the horizontal and 

vertical legs ofthe dilute pneumatic conveying system shown in Figure 3.2. Three kinds of glass beads 

were selected to simulate the pulverized coal and biomass pellets transported in a dilute pneumatic 

conveying system. Detailed information on the cross-sectional spatial distributions of the axial 

particle velocity and particle number rate is reported. In the horizontal part, the experimental data on 

a series of cross-sections clearly illustrate two uniform fluid patterns, annulus structure and stratified 

configuration, which describe the cross-sectional distributions of particle velocity and particle 

number rate respectively. In the vertical pipe behind an elbow R/D=1.3, a horseshoe shape 

characterizes the cross-sectional distribution of axial particle velocity for all three types of glass 

beads on the section OD, close to the elbow outlet. The development of cross-sectional distributions of 

particle number rate indicates that particles with high inertia would be de-entrained from the rope 

formed in a bend. 

5.1 FLUID CONDITIONS AN D MEASUREMEN T PARAMETER S 

The objectives of the experimental investigation are particle dynamic properties like particle 

velocity, particle number rate and their spatial distribution over a pipe cross-section. All of them 

have been measured by employing the extended technique of Laser Doppler Anemometry (LDA) 

which was discussed in Chapter3. The experimental tasks included the measurement of the 

cross-sectional distributions of particle velocity and particle number rate for different particle 

sizes as well as the assessment ofthe effect of particle size on the turbulence intensity of the solid 

phase in the horizontal and vertical parts of the dilute pneumatic conveying system which is 

displayed in Figure 3.2. 

Experiments were performed under the dilute flow regime with three different sizes of glass 

beads and smoke. Three types of glass beads were selected to be transported in pipes by air, 

which were to simulate the dilute gas-solid flow of pulverized coal or biomass pellets. According 

VES017103 
( liaplcr 5 experimental studies of particle dynamics by LDA 

lo the criterion of similarity ol' Stokes Number as introduced in Chapter 2, the first type of glass 

beads (less than 50pm) and the second (70-110pm) correspond to pulverized coal within 

0~110um, as used in power stations. The third group (180~300pm) represents wood-chips 

around I mm size. In addition, smoke was used to track the air phase of the flow in the LD A 

experiments. 

" f i i 

'°20 30 40 EO 80 70 00 90 IO0 110

 !" 20 30 40 SO ffl /0 BO 90 100 110 

(a) by mass (b) by number 

Figure 5.1 Particle distribution for the second type of glass beads. 

As for the second group of glass beads, its real density and bulk density are 2550 kg/m3 and bulk 

density 1569 kg/m1 respectively. These beads were also sorted using 5 different sieve meshes (38, 

45, 75, 90 and 106pm) on a high efficient electric-magnetic shaker. The distributions ofthe mass 

ratio and particle number are shown in Figure 5.1. In producing these results, three particle 

sample volumes of 600ml, 400ml and 200ml were sieved over two hours. According to the mass 

distribution (in Figure 5.1a), most particles are located in the range 90-106pm and the 

corresponding mass is about 90%. If mesh size was considered as the mean diameter o f particles 

grouped in this mesh, the particle number median diameter should be 90 pm where the particle 

cumulative number ratio is more than 50% (as shown in Figure 5,1b). These measured results 

agree with the size precision of 90% in range on the data sheet of glass beads provided by the 

company Worf Glaskugeln GmbH (2008). 

69 
An investigation of particle dynamics in a dilute phase pneumatic conveying system 

5.2 DETERMINING THE PROPE R SAMPLE RATE O F LD A 

In section 3.4, we have discussed the reason why the sample frequency of LD A should be at least 

equal to or greater than l/t rai n (t m i „ is the minimum temporal interval between two adjacent 

particles). Since particle signals recorded by LD A are discrete, there is no theoretical Nyquist 

frequency for a continuous signal and a suitable sampling frequency of LD A must be 

experimentally investigated under different fluid conditions. 

In general, the frequency variation of particles at a point can be described as the local particle 

number rate, particle velocity or particle mass flow rate. Among these three parameters, particle 

number rate is the most proper and evident parameter for expressing particle local frequency 

variation, for it can be directly obtained by counting every available burst signal recorded by 

L D A according to the LD A principle discussed in section 3.1.1. Subsequently, at a measurement 

point, particle number rate against the different sample rate of LD A can be deduced from 

counting burst signals. With regard to a steady gas-solid flow with a constant solid loading ratio, 

the faster the sample rate of LDA , the larger the available burst signals that can be recorded, 

which results in a higher particle number rate. If we observe that particle number rate is no longer 

increased with the sampling rate of LD A beyond a certain value, the current particle number rate 

shows the maximum frequency variation of particles at the measurement point under the current 

fluid conditions. Thus, the suitable sample rate of LD A should be selected as larger than this 

maximum frequency. 

To extend the above discussion relating to a point, to the whole space of a pneumatic conveying 

system, the proper sample rate o f LD A for measurement in a horizontal or vertical pipe will be 

determined when the highest local frequency variation of gas-solid flow is acquired. Due to 

gravity settling, solid phase concentration in the bottom region of the horizontal parts is higher 

than in other parts, even ignoring the effect of elbows in the pneumatic conveying system as 

shown in Figure 3.2. When the proper sample rate of LD A is obtained by experiments at the 

bottom region of the horizontal leg, this sample rate will be suitable for measurements al other 

space in the system as well. 

In our LD A experiments, the second type of glass beads (70-110u.ni), which was used to 

determine the suitable sample frequency of LDA , was conveyed by an air conveying velocity 12 

m/s with solid mass loading ratio (1.6% kgs'Vkgs"1) at the maximum injection speed of the 

screw-feeder, Eleven sample rates of LD A were evaluated at 15 sample points on each y 

coordinate in the lower half of a pipe cross-section (300 mm away from the elbow inlet). The 

measured data of particle number rate at each sample point by the different sample rate were 

70 

VES017105 
Chapter 5 experimental studies of particle dynamics by LDA 

shown in Figure 5.2. 

1500 

y~0 mm 

1000 

•S 500 

2000 

S 1500-

1000 

y=-7.5 mm 

500 

10 20 30 

z(mm) 

40 10 15 20 

z(mm) 

25 30 

4000 

3000 

2000 

1000 

y=-15 mm 

0 

10 20 30 

z(mm) 

40 

100Hz 

300Hz 

500Hz 

800Hz 

1kHz 

2kHz 

3kHz 

4kHz 

5kHz 

Figure 5.2 Particle number rate against the sample rate of LD A on the section 300mm away 

from the elbow inlet air velocity 12m/s, solid loading ratio about 1.6% 

Comparing these three diagrams in Figure 5.2, we notice that the higher the sample rate is, the 

more particles are counted. An d wc also see that particle number rate varies spatially according to 

the different sample rate of LDA . A t a low sample rate equal to or less than 500 I Iz, particle 

number rate is almost the same at 500 counts per second at the different sample points on three 

different y coordinates as shown in the three sub-diagrams of Figure 5.2, It is clear that a 5001 Iz 

sample rate of LD A is too low for experiments. Particle number rate under this sample rate does 

not display its spatial variation due to gravity settling. Increasing the sample rate, we can see that 

particle number rate is also increased not only from pipe wall to pipe centre along the z axis but 

also towards the pipe bottom (along y negative axis). However, particle number rate at each 

sample point is no longer increased rapidly and its value retains only a narrow fluctuation when 

the sample rate of LD A is more than 4 kHz . A s such, 4 kHz is considered as the maximum 

frequency variation of particles on the sample line (y=-15mm) under the current fluid conditions. 

In practice, 10 kHz was empirically selected as the sample rate o f LD A in our experiments with 

consideration of the possibility of particle number rate (larger than 4000, but less than 10000) at 

points close to pipe bottom under the fluid conditions of solid mass loading ratio 1.6% kgs'Vkgs"' 

at a 12m/s air conveying velocity in a tj>75mm pipe. 

71 

VES017106 
A n investigation ol" particle dynamics in a dilute phase pneumatic conveying system 

In addition, for LD A is a single point instrument, a measurement over each cross-section 

consumed about 70 minutes for a measurement interval over one second at every sample point. 

The 10 kHz sample rate ofl.D A will ensure the recording the maximum 10k number ofthe data 

set (Up,, i I, .... N] at each position in one second. Here U p can be one component of the 

particle velocity at the measurement position depending on the optical arrangement of the LDA , 

N is the actual total number of particles crossing the sample point within one second (N<10k), 

which is defined as the particle local number rate. Thus the particle mean velocity at a sample 

point (x, y, z) is given by 

1

 , v 

where {u p x , u p y , u p / f are three particle velocity components and < > represents an appropriate 

average. The particle root-mean-square (RMS) fluctuation velocity is calculated as averaging the 

squared difference between a time-series of local velocities and its mean value at a sample point. 

It can be described by 

where <U' P''> is also representative of the granular temperature 0 which is proportional to the 

square of a random velocity with which the particles oscillate about a mean hydrodynamic 

velocity (Campbell, 1990). Then particle turbulence intensity is expressed as 

(5.3) 

Using the equations outlined above, the experimental data will be analyzed to display the 

cross-sectional properties of particle dynamics along the horizontal and vertical parts of the 

experimental rig. 

5.3 EXPERIMENTAL RESULTS ON PARTICLE DYNAMICS IN A 

HORIZONTAL PIPE 

In Chapter 4, we have demonstrated how to measure the cross-sectional velocity of air phase by 

using the pre-calculated transform matrix to match each shift coordinate o f the traverse system 

with the actual spatial position on the measurement region. 

Similarly, the cross-sectional properties of the solid phase like particle velocity, particle number 

rate and granular temperature were also investigated by means of LD A with a 10 kHz sample rate. 

On each cross-section, a total of 1047 sample points was designed to represent the distribution 

over the whole region. These were accessed through shifting the three-dimensional traverse 
Chapter 5 Experimental studies of particle dynamics by LDA 

system ofthe LDA . Consequently, each section has been meshed into the 1047 local subregions. 

The following subsections will present the experimental results of three types of glass beads 

(<50um; 70-110pm and 1X0~300pm) in the horizontal pipe respectively. 

5.3.1 Features ofthe measured parameters at a typical point 

Among the experimental results ofthe second type of glass beads (70-110pm), Figure 5.3 shows 

the variations of the three components of the particle velocity measured at a typical position on 

the cross-section eight pipe diameters (8><75mm) upstream of the elbow inlet. The typical 

position is located at (0, 25, 0) mm which is marked as the red cross shown in the right hand side 

of Figure 5.3 and is relative to the reference coordinate located at the section centre. Each 

velocity component is a discrete time series recorded by LD A and fluctuates around a mean value, 

for there is no clear increasing or decreasing trend in Figure 5.3. However, the variation of {Up x } 

is much stronger with a covariance of 0.32. The covariance values of {Up y } and {U p z } are 0.11 

and 0.05 respectively. 

N values of a parameter 

48 for U 

px 

66forUp y 

14forUp z 

Covariance 

0.32 for U 

px 

0.11 for U p y 

0.05 for U 

600 

T(ms) 

Figure 5.3 The measured particle velocity at a sample point in three axes 

(Ua=12m/s; particles within the size range 70— 110pm) 

In Chapter 3, we have discussed the refraction effect of the curved pipe wall which makes the 

identical cross-point (at which three pairs of three colour beams of the LD A intersect) separate 

when the crossing point is moved into the pipe. The measurements of the three components of 

{Up X }, {Up y } and {U p z } are not coincident in location, since the actual crossing points ofth e 

three colour beams are (0, 25.10, -1.67) mm for the blue beams (U p x ), (0, 24.98, 1.08) mm for the 

green beams (U p y ) and (0, 25.01, 0.92) mm for the violent beams (U p 7 ). They are grouped around 

the typical point (0, 25, 0) within a 2mm distance. 

73 

VES017108 
An investigation of particle dynamics in a dilute phase pneumatic conveying system 

The total number of measured items for each parameter in one second is considered as the 

particle number rate. Here, the sets JU p x } , {U p y ( and {Vpr} over one second consist of 48, 66 

and 14 items separately. Thus, the measured particle number rates are defined as 48, 66 and 14 

per second. 

Therefore, we will use the statistic time-averaged values of {U p x } , {U p y } , {U p z } and particle 

number rate K to describe the overall variability of solid phase in a local subregion which is 

represented by a typical point. 

5.3.2 Characterizing the experimental data on a pipe cross-section 

Contour of the mean {U } m/s 

<l 13 >1 

1 0-

'•3 12.5 

12 

-40 -20 0 20 40 

z(mm) 

Contour of the mean {U } m/s 

0.01 

-40 -20 0 20 40 

z{mm) 

I o 

b V 

-40 -20 0 20 40 

z(mm) 

Contour of particle number rale {N} 

I o 

-40 -20 0 20 40 

z(mm) 

Figure 5.4 Cross-sectional flow patterns described by the distribudons of particle mean velocitj' 

and particle number rate respectively (Ua=12m/s; particles within the size range 70~T10pm) 

Figure 5.4 displays the time-averaged values of experimental data on the section eight pipe 

diameters upstream of the reference point 15mm before the elbow inlet in the horizontal pipe. 

Among the four diagrams in Figure 5.4, the spatial distribution of the time-averaged particle axial 

velocity |U p x } clearly forms an annular distribution, in which the particle axial velocity 

decreases from the centre of the section to the wall. We call this kind o f fluid pattern an annular 

cross-sectional pattern. Moreover, for the same gas-solid flow on the section, we also observe 

74 
Chapter 5 l:\perimenlal studies of particle dynamics by LDA 

that the particle number rate is represented by a stratified distribution layered from the pipe top to 

the bottom. This strati fied configuration clearly expresses the phenomenon of gravity settling due 

to the gravity force in a horizontal pipe. Aslo an iso-line of the stratification reduces in height 

along the y axis from the pipe right-hand to left-hand side along the z positive direction, which 

means that the particle number rate is larger in the z negative field than in the z positive region 

under the conditions of the identical y coordinate. This inhomogeneous distribution on the z axis 

may be caused by the particles initial conditions, as in the experiments they were horizontally 

injected along the z negative direction by a screw feeder. Thus, the particles will possess an initial 

velocity in the z negative direction after being injected, which results in an initial tendency of the 

particles to move towards the z negative direction. 

As for the other two particle velocity components, {U p y } and {U p z j , their cross-sectional 

distributions do not have any clear pattern, especially for the contour o f {U p y } . In general, the 

time-averaged values of {Up z } over the whole section are positive, which shows the overall 

tendency of particles to move toward the z positive direction. However, the time-averaged values 

of {Up y } may be positive or negative and have a random distribution on the section. 

Therefore, we will use the parameters o f {U p s } , the corresponding granular temperature {0} and 

particle number rate {N} to analyze the cross-sectional experimental data along the fluid 

direction in the following sections. 

5.3.3 The development of cross-sectional fluid patterns in a horizontal pipe 

Under the conditions of air conveying velocity 12m/s and solid mass loading ratio 1.6% and a 

sample rate 10 kHz for Laser Doppler Anemometry, the experimental measurements for the 

second type of glass beads (70-110pm) were performed at a series o f pipe cross-sections 

upstream of the elbow inlet as shown in Figure 5.5. The reference cross-section is defined as OD 

which is 15mm before the elbow inlet. The origin point of every local coordinate system locates 

at the centre of the pipe cross-section. 

The experimental results of time-averaged particle axial velocities {U p v } , granular temperature 

{©} and particle number rate {N} on each cross sections are visualized in the same row in Figure 

5.6. The cross-sectional evolution of these three parameters is subsequently displayed from the 

section 7D to ID along the fluid direction. With regard to cross-sectional fluid patterns, on every 

section from 7D to ID, the annular contour structure of {Up s } and the stratified contours of )N} 

are also clearly observed, resembling the results shown in Figure 5.4. Thus, gas-solid pipe flow 

for solid phase with Stokes number less than 3.6 could be treated as either annular flow or 

75 

VES017110 
An investigation of particle dynamics in a dilute phase pneumatic conveying system 

stratified flow, describing contours of particle axial velocity or particle number rate respectively. 

Figure 5.5 The sketch of eight measurement cross-sections along the horizontal pipe 

Despite the general similarity o f fluid patterns among the cross-sections, the shape, area and 

centre of the annular core (the fastest region) for [U p x j vary along the fluid direction. Moreover, 

the centre of each core is obviously not situated at the corresponding cross-section geometric 

centre of the cross-section, which results in axial asymmetry for the {U p x J cross-sectional 

distribution. Considering the development of the variance of {Up x } or granular temperature {©}, 

we can see an analogous shape on each section. Basically, the variance of fluctuation of {Up x } is 

smaller in the right-up region o f a cross-section, which means a steadier gas-solid flow than in 

the other parts. For the development of particle number rate {N}, a similar layered configuration 

is observed for the cross-sectional distribution of particle number rate on each section. But an 

iso-line of particle number rate varies in actual position with a decreasing trend from the left to 

the right (along the z axis) of each cross-section. This phenomenon shows the effect on the 

behaviour of the downstream gas-solid flow caused by the manner of feeding particles, since the 

particles have minor initial velocities on the z negative axis when they are injected by the screw 

feeder from the pipe right side to the pipe centre. 

Notice: The origin point (O) locates 

at the centre of the OD section 

76 

VES017111 
Chapter 5 Experimental .studies of particle dynamics by LDA 

{II } rn/s al the auction k=7D {<-) } at the section x=7D {H) at the section x=7D 

-40 -20 0 20 40 -40 -20 

z(mmj 

20 40 -40 -20 

{U } m/s at the section x=6D 

z{mm) 

{0} at the section x=6D 

z(mm) 

{H} at the section x=6D 

-40 -20 0 20 40 -40 -20 0 20 40 

2(rnm) 2(mm) 

{U } m/s at the section x = 5D {0} at the section x=5D 

-40 -20 0 20 40 

z(mm) 

{N> at the section x=5D 

-40 -20 0 20 40 

?(mm) 

m/s at the section x-4D 

-40 -20 0 20 40 

z (mm) 

{0 } at the section x=4D {N} at the section x=4D 

-40 -20 0 20 40 

z{mm) 

{U } m/s al the seclion x=3D 

0 20 40 -40 -20 

;(mm) 

{(-) } at the section x=3D 

z(rnm) 

{N} at the section x=3D 

-40 -20 0 20 40 

z (mm) z(mm) 

(Figure 5.6 Continue) 

20 40 -40 -20 0 

z(mm) 

77 

VES017112 
A l l investigation o i particle dynamics in a dilute phase pneumatic conveying system 

(U } m/s at the section x=2D {0 } at the section x=2D 

•40 -20 0 20 

z(mmt 

(U } m/s at the section x=1D 

0 20 

z{mm) 

(0 } at the section x= 1D 

{N} at the section K=2D 

-40 -20 0 20 40 

z(mrn) 

-40 -20 0 20 40 

z(mm) 

0 20 40 

z(mm) 

{N} at the section x=1D 

-40 -20 0 20 40 

z(mm) 

Figure 5.6 Cross-sectional distributions of the mean values of {Upv} and the granular 

temperature {©} (unit: m!/s2) as well as particle number {N} at an air conveying velocity 12m/s 

According to the chart of Geldart for classification of fluidization behaviour (as shown in Figure 

2.2), the three kinds of glass beads used in the experiments can be characterized by their retention 

properties. The first type is less than 50pm, within which glass beads less than 20pm or within 

20~50pni respectively, correspond to Group C materials (with very good permeability) or Group 

A materials on the Geldart chart. The second type of glass beads within 70-110pm also 

corresponds to Group A materials, which have good retention properties and are suitable for 

dense phase pneumatic conveying as well. As for the third type o f glass beads ranging from 1 80 

to 300pm, they are equivalent to Group B materials with very poor air retention capability and 

can de-aerate rapidly when the supply of fluidizing air is shut-off. The empirical minimum 

conveying air velocities in dilute phase suspension flow are about 10~12m/s for transporting 

Group A materials, 13~16m/s for Group B materials and around 3~4m/s for Group C materials 

(Mills D.,2004). 

Since the three kinds of glass beads (density 2550 kg/m') have been used to simulate the flow of 

pulverised coal (0-110pm, density 1550 kg/m3) and biomass pellets (size< 1.0mm, density<800 

kg/m3), these pulverised coal and biomass pellets are effectively Group A materials. But for high 

density and larger granular biomass, the classification is Group B . Here, our experiments mainly 

focus on Group A materials. It is very meaningful to study particle dynamic behaviour in dilute 

phase pneumatic transportation under the minimum air conveying velocity. In this way, it can be 

seen whether the two cross-sectional fluid patterns in the above discussions represent the regime 

78 
Chapter 5 L\pcrimcntal studies of particle dynamics by LDA 

of dilute phase pneumatic conveying in low air velocity. There follows a set of experimental 

results on the same series of cross-sections (as shown in Figure 5.5) under an air conveying 

velocity of lOm/s in the horizontal pipe. 

5.3.3.1 Glass beads less than 50|jm (the first type) 

Glass beads of the first type are less than 50pm in diameter and their Stokes Numbers are also 

less than 3.6. On the whole, these kinds of particles have a good ability to follow the air flow. For 

these fine particles, the corresponding particle number rate is drastically larger than the other two 

types under the same solid mass loading. In order to keep the same sample rate 10 kHz of LD A 

for the three types of glass beads, the solid mass loading ratio forthe first type is only 1/10 that of 

the other two types whose solid mass loading ratios are about 1.9% under an air conveying 

velocity of lOm/s in o)75mm pipe. 

Figure 5.7 and 5.8 visualize the cross-sectional experimental data of the first type of glass beads 

on the sections from 7D to OD. In order to make these experimental data on different sections 

comparable, the axial particle velocity and the particle number rate are separately normalized by 

air conveying velocity (Ua ) and the total number rate (ZN) on each cross-section. 

In Figure 5.7, the development o f the cross-sectional distributions of the dimensionless axial 

particle velocity {Upx/Un} is illustrated along the fluid flow direction. The contours of {Up x /Ua } 

apparently display a similar annular form, especially on the sections from 7D to ID. In these 

contours, each annular core with an iso-line value of 1.2 is around the section centre with a slight 

deviation towards the z positive axis. The iso-line value o f {Up x /Ua } shows clearly decreasing 

tendency from pipe centre to pipe wall. But the area within an iso-line may be different 

dependent on the detailed cross-section. Although the annular form is also shown in the contour 

of {Up x /Ua } on the section OD, the key difference with those on the other sections lies in that the 

annular core is shifted beyond the pipe centre and its iso-line value is increased as 1.3 on the 

section OD. This difference must be caused by the effect of the bend on the upstream fluid flow, 

for the section OD is 15mm upstream from the bend inlet. On the whole, in terms of the similarity 

among the cross-sectional distributions of {Up x /Ua }, the dilute suspension flow of glass beads of 

the first type can be treated as being fully developed and steady in the horizontal pipe before one 

pipe diameter of the bend. 

79 

VES017114 
A n investigation of particle dynamics in a dilute phase pneumatic conveying system 

Figure 5.7 Development of cross-sectional distributions of the dimensionless axial particle 

velocity {Upx /Ua } of the first type of glass beads (<50um) under an air conveying velocity 

Ua=10m/s and the solid mass loading ratio 0.19%. 

80 

VES017115 
Chapter 5 Lxperimcntal studies ofparticle dynamics by LDA 

40 

20 

-20 

-40 

4 0 , 

20 

-20 

-40 

40 

20 

-20 

-40 

40 

20 

-20 

-40 

7D 

Natural logarithm of the dimensionless particle number rate {ln(N/£N)} 

- 40 r 

-7 

•6 

t 

5D 

9 

•95 

2D 

'-6 # 

OD 

-AA . 

tl tr. 

-50 

•S -7 ' 

V 

0 

z(mm) 

20 

-20 

-40 

40 

20 

-20 

20 

-20 

-40 

6D 

•9 

4D 

1D 

-50 0 

4mm) 

50 

50 

-9 -8 -7 -6 -I 

e \ x=-9, -8,-7,-6,-5,-4 

nx10" 4,n=2,4,10,25, 68,184 

Sections Total (N}(x105) 

0D 3.13 

1D 4.69 

2D 9.40 

4D 3.98 

5D 6.38 

6D 4.60 

7D 3.27 

-4 -3 

Figure 5.8 Development of cross-sectional distributions of the dimensionless particle number 

rate {ln(N/£(N))} of the first type of glass beads (<50pm) under an air conveying velocity 

L

i

11=10m/s and the solid mass loading ratio 0.19%. 

By contrast, Figure 5.8 shows the cross-sectional distributions of the natural logarithm of the 

81 

VES017116 
An investigation of particle dynamics in a dilute phase pneumatic conveying system 

dimensionless particle number rate jln(N/X(N))} from the section 7D to OD. The contours of 

particle number rate |N | in Figure 5.8 not only generally illustrate the stratified configuration on 

each section, but also clearly show the different layered shape of each contour varying along fluid 

direction. On the section 7D, the largest value ofparticle number rate is in the region close to the 

bottom-left of the section. Then this region gradually expands towards the section bottom until 

the section 5D. The contour iso-line of -7, which is corresponding to lOxlO" 4 of the total particle 

number rate, remains near the centre (y=0) of the pipe until the section ID. But the regions 

layered by iso-lines show some fluctuations. This fluctuation indicates the different frequency of 

particle-wall collision on each section. Due to gravity, particles with small Stokes Number still 

have a falling tendency. As such, the larger the region with maximum particle number rate means 

the more the particles are concentrated, which may cause a higher frequency of particle-wall 

collision. When particles are re-suspended towards the pipe centre due to the Saffman force and 

the effect of particle-wall collision, the region with the maximum particle number rate on the next 

adjacent section will be decreased. This variation also shows that the gas-solid pipe flow o f the 

first type of glass beads is heterogeneous and unsteady, which is contrary to the result deduced by 

the variations o f {U p x / U a } . Therefore, the gas-solid flow formed by the first type of glass beads 

shows steady and unsteady state simultaneously dependent on which parameters are used to view 

it. 

5.3.3.2 Glass beads within the range 70 to 110 |itn (the second type) 

The second type of glass beads range from 70 to 110 pm and the corresponding Stokes Number 

varies within 10-28. Compared with the first type, glass beads of the second type have higher 

inertial properties and they usually keep their own track rather than following fluid like the 

particles of the first type. Under an air conveying velocity of lOm/s and solid mass loading ratio 

1.9%, the measured experimental data on the sections from 7D to ID (as shown in Figure 5.5) are 

illustrated in Figure 5.9 and Figure 5.10. 

In Figure 5.9, an annular form is also observed on each cross-sectional distribution of the 

dimensionless axial particle velocity {U p x / U a } of the second type of glass beads (70-110pm). 

Overall, this annular form, in which the axial particle velocity decreases from the annular core to 

the pipe wall, resembles that shown in Figure 5.7. But the iso-line value and position of the 

annular core are different in the two figures. From the section 7D to ID, each centre of the 

annular cores with an iso-line value of 1.35 in Figure 5.9 is beyond the pipe centre, which is 

different from the observation that every centre of the annular core with an iso-line value of 1.2 is 

shifted towards the z positive axis in Figure 5.7. In the main stream region of each cross-section, 

the values of iso-lines from pipe centre to pipe wall are larger in Figure 5.9 (1.35-1.0) than those 

82 

VES017117 
Chapter 5 Kxperimcnta! studies of particle dynamics by LDA 

in Figure 5.7 (1.2-0.8). Thus, the area-averaged axial particle velocity of the second type of glass 

beads should be faster than (hat ofthe first type of glass beads on the sections from 7D to ID. 

The dimensionless axial particle velocity {U X /Ua} 

40 r- 40 : — 

V" 

-60 -40 -20 0 20 40 

z{mm) 

Figure 5.9 Development of cross-sectional distributions of the dimensionless axial particle 

velocity {Upl/U,} ofthe second type of glass beads (70~110u.m) under an air conveying velocity 

Ua=10m/s and the solid mass loading ratio 1.9%. 

83 

VES017118 
An investigation oi'particle dynamics in a dilute phase pneumatic conveying system 

Nalural logarithm of the dimensionless particle number rate {ln(N/£N)} 

40 

•3 

SD 

4F 

-40 

40 

-40 

40 

-40 

40-

1D 

-40 -20 0 20 

z(mm) 

-40 

40 

e*, x=-9,-8,-7,-6,-5,-4 

Ox10"\n=2.4. 10,25,68 . 184 

Sections Total{N)(,10s) 

1D 3.51 

2D 3.91 

3D 1.94 

4D 190 

50 1.95 

6D 1,80 

7D 1.92 

Figure 5.10 Development of cross-sectional distributions of the dimensionless particle number 

rate Jln(N/X(N))} of the second type of glass beads (70~110u.m) under an air conveying velocity 

Ua=10m/s and the solid mass loading ratio 1.9%. 

Similarly, the stratified configuration observed in Figure 5.7 can be also found in Figure 5.10, 

which di.splays the development o f cross-sectional distributions o f the dimensionless particle 

number rate (ln(N/S(N))} for the second type of glass beads (70-110pm). This layered feature 

demonstrates the phenomenon of gravity settling due to gravity force which makes particles 

concentrate close to the bottom region in a horizontal pipe. On the sections from 7D to ID, the 

stratified iso-lines of each cross-sectional distribution of (ln(N/I(N))} in Figure 5.10 are different 

VES017119 
Chapter 5 hxperimenlal studies ofparticle dynamics by LDA 

from those in Figure 5.8. A comparison or them shows that the total number of layers in Figure 5.10 is 

more than that in Figure 5.8 with the same interval of 0.5. And the maximum value of )ln(N/X(N))} 

occurs at the left-bottom of each section in Figure 5.8. In contrast, the maximum value of 

|ln(N/ I(N))j in Figure 5.10 is nearly close to the bottom centre of each section with little deviations 

towards the left-hand side. Third, ihe iso-linc with the value of-7 , which is corresponding to lOxlO" 4 

of the total particle number rate of each section, varies around the pipe centre line of y=0mm from the 

section 7D to ID in Figure 5.7. This corresponding iso-line in Figure 5.10 is below but close to the 

pipe centre line of y=0mm. 

5.3.3.3 Glass beads within the size range 180~300|jm (the third type) 

Glass beads in the third type vary within the size range I80~300pm. Figure 5.11 shows the 

experimental data measured by LD A on the cross-sections from 7D to 1D (as shown in Figure 5.5) 

under an air conveying velocity of 1 Om/s and solid mass loading ratio 1.9%. 

As for cross-sectional distributions of the dimensionless axial particle velocity {U p «/U a }, the 

annular feature is not apparently shown in Figure 5.11, which is compared with that in Figure 5.7 

or Figure 5.8. With the same interval value of 0.5, the spatial distribution of {U p x / U a } on each 

section in Figure 5.11 can be divided into the inner circle and the outer ring by the iso-hne of 1.2. 

Unlike the other two types of glass beads, there is no annular core with the maximum value of 

{ U p x / U a } for the third type of glass beads in Figure 5.11. The areas bounded with the value of an 

iso-line larger than 1.2 are just randomly distributed within the inner circle of each section. 

Since the maximum values of {U p x / U a } are separately 1.2, 1.35 and 1.4 for the first, the second 

and the third types of glass beads, this denotes an interesting phenomenon that larger glass beads 

have obtained faster maximum axial particle velocity under the same air conveying velocity. 

According to the experimental results of Tsjui et al. (1982), air flow turbulence was reduced by 

plastic particles of a mean size 210|jm (the range I00~400pm; density 1000kg/m3). As such, the 

kinematic energy of air flow or air velocity may be increased due to the lessening turbulent 

energy. Thus, an increasing air velocity would also make the second and the third type of glass 

beads accelerate faster. 

Nevertheless, the above explanation need to be confirmed by the further experimental data, 

especially the simultaneous measurement data of two phase velocities in gas-solid pipe flow with 

different particle size. 

85 

VES017120 
An im csligation of panicle dynamics in a dilute phase pneumatic conveying system 

Relative velocities ofthe axial particle velocity {U /U } 

40 • —- 40 

z(mm) 

Figure 5.11 Development of cross-sectional distributions of the dimensionless axial particle 

velocity {Upj/Ua} of the third type of glass beads (180~300um) under an air conveying velocity 

Ua=10m/s and the solid mass loading ratio 1.9%. 
I haplcr 5 l.xpcrimental studies ofparlicle dynamics by LDA 

Natural logarithm of the dimensionless particle number rate {ln(N/iN)J 

40 ---.-1 40 

Figure 5.12 Development of cross-sectional distributions of the dimensionless particle number 

rate {ln(N/ E(N))} of the third type of glass beads (180~300(nm) under an air conveying velocity 

Ua=10m/s and the solid mass loading ratio 1.9% 

As for the third type of glass beads, Figure 5.12 shows the development of cross-sectional 

distributions of the dimensionless particle number rate {ln(N/X(N))j from the section 7D to ID. 

87 
An investigation ol'particle dynamics in a dilute phase pneumatic conveying system 

Compared with thai in Figure 5.8 and Figure 5.10, the stratified configuration can be still observed on 

each section in Figure 5.12. With the same interval of {ln(N/ 2(N))}, the total layer in Figure 5.12 (the 

third type of glass beads) is larger lhan thai in Figure 5.8 (the first type of glass beads), but less than 

thai in Figure 5.10 (the second type of glass beads). The iso-line with the value of-7 , which is 

corresponding to lOx 10"' ofthe total particle number rate of each section, is away from the pipe centre 

line of y=0mm and varies around the height of 1/4 pipe diameter from the pipe bottom. In addition, 

the distribution of iso-lines of {ln(N/ X(N))} does not strictly decrease from the top to the bottom on 

each section in Figure 5.12. The regions with the relative larger values, close to the maximum value of 

jln(N/ I(N))}, is not only located in the pipe bottom but also found around the pipe top wall. This 

phenomenon is not shown in Figure 5.8 or Figure 5.10. Moreover, there exists some symmetry along 

the pipe vertical centre line of z=0mm in Figure 5.12. This symmetric property is different from the 

experimental results observed in Figure 5.8 and Figure 5.10. It indicates that the inertia effect on 

dynamic behaviour of glass beads in the third type is much stronger. 

5.4 PARTICLE DYNAMIC BEHAVIOUR IN A VERTICAL PIPE 

DOWNSTREA M OF A 90° ELBO W 

The roping phenomenon is one of great interest in pneumatic conveying research. It occurs in a 

bend and results in particles being concentrated within a small portion of one pipe cross-section 

at the bend, as well as in the pipe downstream of the bend, due to particle inertia. Consequently, 

it is very important to study the Rope disintegration processing after a bend before dual or triple 

branches are used to deliver particles in a controllable way to the various burners in a pulverized 

fuel (PF) boiler. Furthermore, the extended technique of Laser Doppler Anemometry has been 

applied to determine not only the spatial change in the particle velocity distribution but also to 

characterize the particle segregation, as shown by particle number rate, in a bend. 

As for the characteristics of air flow in a vertical pipe downstream of a bend, experimental and 

numerical data of cross-sectional distributions of the axial air velocity {Ua y } and the horizontal 

air velocity {U M } have been discussed in Chapter 4. The cross-sectional distribution of the axial 

air velocity \Uay \ on the section 0D displays a horseshoe shape, where {Ua y } is slower inside 

(pipe inner wall) and faster outside (pipe outer wall). This feature can be still observed on the 

further downstream sections. But the difference of {Ua y } between inside and outside the 

horseshoe tends to be lessened. Moreover, a secondary flow described by {U a x ( is formed on the 

section OD and gradually becomes weak till it has completely disappeared. 

88 

VES017123 
Chapter 5 1-AperimeMal studies o f particle dynamics by LDA 

Nulice: The origin point (O) locates 

al 'he centre of the OD section 

Figure 5.13 The arrangement of measurement cross-sections in the vertical pipe 

In the following sections, the experimental data of three types of glass beads, pneumatically 

transported from a horizontal pipe section through an elbow (R/DH.3 ) into a connecting vertical 

pipe, have been measured by the extended technique of Laser Doppler Anemometry discussed in 

Chapter 3. A total of seven cross-sections along the vertical pipe are schematically illustrated in 

Figure 5.13 and the reference cross-section (OD) is about 15mm away from the elbow outlet. The 

distance between two adjacent cross-sections is equal to one pipe diameter. 

5.4.1 Glass beads less than 50u,m (the first type) 

With regard to the first type of glass beads (<50pm), the experimental data measured by LD A on 

the cross-sections from OD to 6D in the vertical pipe are illustrated in Figure 5.11, Figure 5.12 

and Figure 5. 13 for the dimensionless axial particle velocity {U p y / U a j , the dimensionless 

horizontal particle velocity {Up x /max(abs(Up !J)} and the dimensionless particle number rate 

jln(N/'Z(N))} respectively, under an air conveying velocity lOm/s and solid mass loading ratio 

0.19%. 

89 
An investigation ofparticle dynamics in a dilute phase pneumatic conveying system 

In Figure 5.14, the horseshoe shape can be found on each contour of {U p y / U a } from the section 

OD to 4D. This feature is similar to that shown in contours of the axial air velocity {Ua y } in 

Figure 4.5. Generally, the axial particle velocity {U p y [ is faster on the outside portion of the 

horseshoe (towards pipe outer wall) than that on the inside portion of the horseshoe (towards pipe 

inner wall). At the further downstream sections of 5D and 6D, the horseshoe-shaped feature no 

longer exists and the cross-sectional distributions of {U p y / U a } have developed into another 

pattern where a small region with the slower {Up y } is surrounded a ring with the faster {U p y } . In 

addition, the region with the slowest {Up y } on a section is close to the pipe right wall (the z 

positive direction) behind the section ID and its area is gradually enlarged from the section 1D to 

5D. A similar distribution can be found between the contour of {U p y / U a } on the section 5D and 

that on the section 6D. Also the maximum value of {U p y / U aj on both sections is decreased as 1 

from 1.3 on the section OD. The similarity suggests that gas-solid flow of the first type of glass 

beads begin to be steady from the section 5D. 

With regard to the dimensionless horizontal particle velocity {Up x /max(abs(Up x ))} of the first 

type of glass beads (<50u.m), Figure 5.15 shows the development of the cross-sectional 

distribution of {Up v /max(abs(Up x ))}from the section OD to 6D in the vertical pipe downstream of 

a bend. It is very clear that the secondary flow of the first type of glass beads shown in Figure 4.7 

(for the single air phase) can be also observed in Figure 5.15. On each section, we assume the 

pipe inner wall as the start position, where the secondary flow runs towards the pipe outer wall 

with a decreasing tendency of {U p x } . When the secondary flow reaches at the pipe outer wall, 

{ U p x } is close to zero. Then this secondary flow changes its fluid direction from the x positive 

axis to the x negative axis and it is developed into two subflows which run towards the pipe inner 

wall with an acceleration along the pipe left wall and the pipe right wall respectively. As such, the 

secondary flow forms two subcirculations of one counter-clock-wise and one clock-wise 

separately. From the section OD to 6D, the key difference between secondary flows is that the 

region with the positive maximum {Up x /max(abs(Up x ))J is gradually shifted from the pipe inner 

wall to the pipe centre and the total number of iso-lines is reduced. 

"0 

VES017125 
Chapter 5 L.xpcrimenlal studies of particle dynamics by LDA 

40 

Dimensionless axial particle velocity {Up y /Ua} 

OD 

20 

-20 

-40 

40 

r f . • 

OQ5 ' ' ' 

2D 

20 

-20 -

-40 

40 -

OS's" 

4 

4D 

20 -

-20 

-40 

40 

6D 

20 

-20 • 

7 

1D 

20 

-20 

-40 

40 

3D 

20 

-20 

-40 

40 

5D 

20 

-20 

-40 

' 1 

-50 0 50 

z(mm) 

0.2 0.4 0.6 0.8 1 1.2 

U =10(m/s) 

-40 

-50 0 

z(mm) 

50 

Figure 5.14 Development of cross-sectional distributions of the dimensionless axial particle 

velocity {Up y /U„} of the first type of glass beads (<50u,m) under an air conveying velocity 

Ua=10m/s and the solid mass loading ratio 0.19% in the vertical pipe behind an elbow (R/D=1.3) 

91 

VES017126 
An investigation ofparticle dynamics in a dilute phase pneumatic conveying system 

40 

20 

OD 

-20 j 

-40 i 

40 ; 

20 

-20 

2D 

-40 • 

40 

20 

-20 

20 

4D 

The dimensionless horizontal particle velocity {Up x /max(abs(Up x ))} 

tus 

9> 4 

6D 

-20 

-40 

( ' 

/ \ U 

v \ ( 

V, 

-50 0 

z(mm) 

40 

20 

-20 

20 

-20 

20 

-20 

1D 

3D 

5D 

-40 

-50 

' US 

. ) Z 

3 % & 

Pe 

06 

'O , 

-1 -0.5 

0 

z(mm) 

0 

50 

50 

Sections Maximum absCU^XnVs) 

OD 2.26 

1D 2.14 

2D 1.71 

3D 1.61 

4D 1.44 

5D 1.24 

6D 1.48 

Figure 5.15 Development of cross-sectional distributions of the dimensionless horizontal particle 

velocity {Ups/max(abs(Ups))) of the first type of glass beads (<50um) under an air conveying 

velocity Ua=10m/s and the solid mass loading ratio 1.9% in the vertical pipe behind an elbow 

(R/D=1.3) 

92 

VES017127 
Chapter > Hxpcrimcntal studies of particle dynamics by LDA 

40 

Natural logarithm ofthe dimensionless particle number rate (ln(N/i(N))} 

40, 

iOD - 7 ? 

20) 

'Jo' 

-201 t 

-40 

40 

2D 

-8. 

20 

-20 

-40 t 

40 r 

4D 

20 

-20 

-40! 

4 0 , 

6D 

20 

-20 

' % :r. aMMHMta ^ 

. " 7 -7 -5 

-40 

-50 0 

z(mm) 

20 

-20 

20 

-20 

20 

-20 

1D 

-8 -6 

3D 

• f f 

-40 

5D 

-50 0 

z(mm) 

50 

50 

-10 -9 -8 -7 -6 -5 

e*, x=-9,-8, -7,-6,-5,-4 

nx10" 4,n=2,4.10,25,68,184 

Sections Total (N) (105) 

0D 540 

1D 2.57 

2D 4.98 

3D 5.15 

4D 4.54 

5D 3.68 

6D 3.35 

Figure 5.16 Development of cross-sectional distributions of the dimensionless particle number 

rate {N/S(N)} ofthe first type of glass beads (<50pm) under an air conveying velocity Uo=10m/s 

and the solid mass loading ratio 1.9% in the vertical pipe behind an elbow (R/D=1.3) 

93 
Al) investigation ol' particle dynamics in a dilute phase pneumatic conveying system 

Figure 5.16 displays the experimental data of the dimensionless particle number rale 

jln(N/ L(N))|, which is normalized by the summation of particle number rate on each section, 

from the section OD to 6D in the vertical pipe. Overall, the feature of stratified configuration or 

any other uniform pattern can not be observed on cross-sectional distributions of {ln(N/ S(N))} in 

Figure 5.16. On the section OD, referring to the horseshoe shape of (U p y / U a } as shown in Figure 

5.14, we can see that the relatively dense particle number rate with the iso-line value of -6 is 

positioned closed to the outside portion of the horseshoe (the pipe outer wall). In contrast, the 

region with the smaller value (-7) of jln(N/X(N))} is located i n either the pipe left-inner or 

right-inner wall. On the section ID, the contour of {ln(N/X(N))} resembles with that on the 

section OD. But the area within an iso-line may be shifted. At further downstream sections, the 

contours of {ln(N/X(N))} are developed to be randomly distributed with no clear shape. On the 

section 5D or 6D, the region with the higher relative density {ln(N/X(N))) is shown at the pipe 

right-inner wall with the smallest value of {U p y / U a } . On the whole, the rope of relative dense 

particle number rate formed in the bend has still not dispersed by the section 6D for the first type 

of glass beads transported by a 1 Om/s air conveying velocity and solid mass loading ratio 0,19% . 

5.4.2 Glass beads within the size range 70~110u,m (the second type) 

Experiments using the second type of glass beads were performed to measure cross-sectional 

distributions of the axial particle velocity {U p y } , the horizontal particle velocity {U p „ j and 

particle number rate {N} on the same series of cross-sections as discussed in the proceeding 

section. Under fluid conditions o f air conveying velocity lOm/s and solid mass loading ratio 

1.9%, the experimental data on cross-sectional distributions o f three parameters from the sections 

OD to 6D are shown in Figure 5.17, Figure 5.18 and Figure 5.19 

As for the dimensionless axial particle velocity {U p y / U a } , Figure 5.17 shows the development of 

its cross-sectional distributions in the vertical pipe downstream of the bend. The 

horseshoe-shaped feature can be also observed on the contours of {U p v / U a } from the section OD 

to 4D, but it is no longer apparent on the contours of {U p y /L' a J at the further sections of 5D and 

6D. However the contour shape o f {U p y / U a } is identical to that on the section 6D, which 

indicates a steady state of gas-solid flow for the second type o f glass beads after the section 5D. 

A l l the above observations have a good agreement with those observed in Figure 5.14 for the first 

type of glass beads. At a point on each cross-section, the axial particle velocity ofthe first type in 

Figure 5.14 tends to be the corresponding local axial air velocity in Figure 4.5. But it is less than 

that ofth e second type in Figure 5.17. This phenomenon shows the inertia effect on particle 

dynamics, since the first type (<50pm) has a smaller Stokes Number than the second type 

94 
Chapter s Lxperi mental studies ofparticle dynamics by LDA 

(70-1 10pm) does. As such, after being accelerated by the fastest air flow, the second type of 

glass beads would retain its state with a high velocity and the first type tends to follow the current 

local air How when both glass beads enter into a region with lower air velocity. 

Figure 5.18 shows the development of cross-sectional distributions of the dimensionless 

horizonlal particle velocity (Up x /Ua } from the section OD to 6D. Clearly, the characteristic of 

secondary flow is also shown in Figure 5.8, especially at the sections of 2D to 6D. Compared 

with those in Figure 5.15, the feature of secondary flow is not clear in the contours of {Up x /Ua } 

on the section OD and ID in Figure 5.18. But we can still see the increasing tendency o f the 

magnitude of {U^/th,} towards the x negative axis along the pipe left-hand wall and the pipe 

right-hand wall respectively. In addition, for the second type of glass beads, the magnitude of 

{Up x /Ua } in Figure 5.18 is generally larger in the x negative direction than in the x positive 

direction. But the magnitude of {Up x /Ua } in the x positive direction obviously increases from the 

section OD to 6D. By contrast, for the first type of glass beads, the magnitudes of {Up x /Ua } in 

both x directions are nearly equal on each cross-section (as shown in Figure 5.15). 

With regard to the dimensionless particle number rate {N/Z(N)), Figure 5.19 shows the 

development of its cross-sectional distributions from the section OD to 6D. On the section OD, the 

rope ofthe region with the maximum {N/'Z(N)} is shown at the pipe outer wall. Additionally, a 

stratified configuration shows that (N/X(N)} decreases from the pipe outer wall to the pipe inner wall. 

This stratification feature was not found in thebehavour of the first type of glass beads in Figure 5.16. 

At the further sections downstream o f OD, the total contour number of (N/£(N)} gradually decreases 

while both the dense region with the maximum {N/Z(N)} of-6 and the dilute area with the minimum 

{N/Z(N)i of- 9 are smaller and smaller. In particular, downstream of the section 4D, the dense region 

with the iso-line value of-6 is lessened like a curved strip located around the pipe left-inner wall and 

the cross-sectional distributions of {N/X(N)} are developed into a simple pattern in which a relatively 

dilute region with the iso-line value of -8 is surrounded by a relatively dense region with the iso-line 

value of -7 over the main area ofthe section 5D and 6D. 

Therefore, the gas-solid flow of the second type of glass beads can be considered as being steady 

downstream of the section 4D, according to the similarities o f cross-sectional distributions of 

{Upy/L'a} and |N/Z(N)}. In addition, the development of the cross-sectional distributions of 

|N/Z(N)} indicates that the rope ofth e second type of glass beads is still retained until the section 

6D, where a dense region with the maximum {N/Z(N)| is located at the pipe left-inner wall. 

95 

VES017130 
A n investigation ofparticle dynamics in a dilute phase pneumatic conveying system 

Figure 5.17 Development of cross-sectional distributions of the dimensionless avial particle 

velocity {Up v /U0 ( of the second type of glass beads (70~110nm) under an air conveying velocity 

Ua=T0m/s and the solid mass loading ratio 0.19% in the vertical pipe behind an elbow (R/D=1.3) 

96 

VES017131 
Chapter 5 hxperimental studies ofparticle dynamics by LDA 

Figure 5.18 Development of cross-sectional distributions of the dimensionless horizontal particle 

velocity {UpS/max(abs(Ups))} of the second type of glass beads (70~110u.m) under an air 

conveying velocity Ua=10m/s and the solid mass loading ratio 1.9% in the vertical pipe behind 

an elbow (R/D=1.3) 

97 

VES017132 
An investigation of particle dynamics in a dilute phase pneumatic conveying system 

40 

Natural logarithm of the dimensionless particle number rate {ln(N/l{N))} 

OD 

20 

-20 

-40 

40 

* .6 

2D 

20 

-20 

-40 

40 

3*. 

-6 

4D 

20 

-20 -

-40 • 

40 

6D 

20 

-20 

-40 

-50 

• A 

/ a' 

z(mm) 

40 

1D -7& 

\ 20 

-20 

>5 -6 

4^ 

-40 < 

40 , 

3D 

20 

-20 

-40 

40 

Jo 

5D 

20 

-20 

3 5-s -1 

-40 

-50 

50 

0 

z(mm) 

-10 -9 -8 -7 -6 -5 

e \ x=-9,-8,-7,-6,-5,-4 

nx 10" 4,n=2,4, 10,25,68, 184 

Sections Total {N) (105) 

0D 2,55 

1D 2.64 

2D 2.38 

3D 2.36 

4D 2.54 

5D 3.13 

6D 2.94 

50 

Figure 5.19 Development of cross-sectional distributions of the dimensionless particle number 

rate {N/X(N)} of the second type of glass beads (70~110um) under an air conveying velocity 

Ua=10m/s and the solid mass loading ratio 1.9% in the vertical pipe behind an elbow (R/D=1.3) 

98 

VES017133 
Chapter 5 Kxpcri menial studies ofparticle dynamics by LDA 

5.4.3 Glass beads within the size range 180~300u,m (the third type) 

The experiments were performed using the third type of glass beads within the size range 

1 X0~300pm, which were transported in the pipe by an air conveying velocity lOm/s with a solid 

mass loading ratio 1.9%. The experimental data are plotted in Figure 5.20, Figure 5.21 and Figure 

5.22 respectively. 

As for the dimensionless axial particle velocity {U p y / U a } , Figure 5.20 shows the development of 

its cross-sectional distributions from the section OD to 6D in the vertical pipe downstream of the 

bend. In general, the horseshoe-shaped feature is observed in contours of {U p y / U a ) before the 

section 3D. Further downstream, a clear shape can no longer be observed on contours of {U p y / U a } 

on the sections of 4D to 6D, where {U p y / U a | is much more randomly distributed and has a larger 

value (more than 1) in the main area of a cross-section. Comparing Figure 5.20 with Figure 5.14 

(the first type glass beads) and Figure 5.17 (the second type o f glass beads) as well as Figure 4.5 

(air flow), we list their key difference and similarity i n Table 5.1. 

Table 5.1 Comparisons of the axial velocity distributions in a vertical pipe downstream 

of a bend among three types of glass beads and air flow 

A ir flow 

« U a / U a } ) 

Glass beads ({U r y A ir flow / U „ [) 

« U a / U a } ) The first type 

(<50um) 

The second type 

(70-110 urn) 

The third type 

(180-300 nm) 

Stokes Number - <3.5 10-28 >35 

Horseshoe-shaped feature 

observed on the sections 

from OD to 7D from OD to 4D from 0D to 4D from OD to 2D 

on 

the 

sect 

ion 

6D 

Region with the 

smallest axial 

velocity close to 

the pipe 

right-inner wall 

the pipe right wall the pipe left-inner 

wall 

on the pipe left wall 

the 

sect 

ion 

6D 

The values of 

iso-line in the 

main area of the 

section 6D 

>=1 >=0.95 >=!.! >-1.2 

Obviously, the horseshoe-shaped feature is a common characteristic in contours of the axial 

velocity {U„/U a ) or {U a ) / U a } in the vertical pipe downstream of a bend for both air flow and 

gas-solid flow of three types of glass beads. This feature is still observed at the section 7D for air 

flow, By contrast, it disappears at the downstream of the section 4D for the first and second types 

of glass beads and at the downstream of the section 2D for the third one. Therefore, this 

horseshoe-shaped feature must be formed due to the bend effect which changes a horizontal flow 

of air or gas-solid into the vertical one. The different dispersion positions of the horseshoe 

indicate that particle Stokes Number influences the cross-sectional patterns of lU a y / U a } in a 

vertical pipe behind an elbow. In addition, for the axial particle velocity of three types of glass 

beads on the main area of the section 6D, it shows that a larger glass bead has a higher axial 

99 
An investigation ofparticle dynamics in a dilute phase pneumatic conveying system 

Figure 5.20 Development of cross-sectional distributions of the dimensionless axial particle 

velocity {Up y /U0 [ of the third type of glass beads (180~300um) under an air conveying velocity 

Ua=10m/s and solid mass loading ratio 0.19% in the vertical pipe behind an elbow (R/D=1.3) 

100 
Chapter S hxpcri mental studies ofparticle dynamics by LDA 

40 

The dimensionless horizontal particle velocity {U /max(abs(U ))} 

OD 

2D 

4D 

1 

6D 

-20 i 

-40 

-50 

WgMm 

t 

f 

v 

V 

o 

z(mm) 

50 

40 

20 

-20 

20 

-20 

-40 

40 

20 

-20 

1D 

* 1 

3D 

5D 

-40 

-50 

-1 -0.5 

•4 

o 

z(mm) 

50 

0.5 

Sections Maximum abs(Ly(rrVs) 

0D 

ID 

2D 

3D 

4D 

5D 

6D 

2.02 

2.15 

1.37 

1.93 

0.93 

1.18 

2.07 

Figure 5.21 Development of cross-sectional distributions ofthe dimensionless horizontal particle 

velocity {Upj/max(abs(Upj))( of the third type of glass beads (180~300um) under an air 

conveying velocity Ua=10m/s and the solid mass loading ratio 1.9% in the vertical pipe behind 

an elbow (R/D=1.3) 

101 

VES017136 
An investigation ofparticle dynamics in a dilute phase pneumatic conveying system 

Contours ofthe dimensionless horizontal particle velocity {Up x /max(abs(Up x ))! from the section 

OD to 6D are displayed in Figure 5.21. Unlike those of the other two types of glass beads, each 

contour of the third type does not show the feature of secondary flow in the vertical pipe 

downstream of the bend. Overall, there is no clear form shown in contours of 

{Up x /max(abs(Up X ))j on the sections of OD, ID and 6D. But a similar structure can be seen on 

the sections from 2D to 4D. Contours of {Up x /max(abs(Up x ))} on these sections illustrate that a 

strip in the middle of the section divides it into three parts along the x axis. Basically, 

{Up x /max(abs(Up x ))} is almost zero in the strip and negative in both sides of the strip. Moreover, 

the magnitudes of {Up x /max(abs(Up x ))} have no significant discrepancy on all sections, 

especially on the section 6D, where {Up x /max(abs(Up x ))} is almost homogenously distributed 

with a value of zero over most of the area of the section. Compared with Figure 5.15 and Figure 

5.18, the key difference lies in the lack of structure of secondary flow in Figure 5.21. This 

indicates that air secondary flow (the horizontal air velocity) has much more influence on the first 

and the second types of glass beads than on the third one. 

The evolution of cross-sectional distributions of the dimensionless particle number rate (N/Z(N)} 

is shown in Figure 5.22. Generally, there is no uniform or clear pattern in any contours of {N/Z(N)j 

from the section OD to 6D. In most regions of a whole section, (N/Z(N)} has a relative small value of 

-7 or -8, which are corresponding to 10 or 4 xlO" 4 ofthe total particle number rate on this section. The 

rope, which is formed by the region with the maximum particle rate, is the most frequently but 

sporadically located along the pipe left wall and each region only occupies a small fraction similar to 

several discrete circles on the whole section. This is different from the experimental results observed 

in Figure 5.16 and Figure 5.19 for the first and the second types of glass beads, for both types of glass 

beads at least have a clear form shown in the contours of {N/£(N)} on the section OD. This difference 

among three types of glass beads also indicates lhat particle inertia plays an important influence on 

particle dynamic properties in a vertical pipe downstream of a bend, for the third type of glass beads 

with the largest Stokes Numbers tends to retain their previous state at the elbow outlet, when they 

enter into the vertical pipe from the elbow. And the other two types will be easily influenced to follow 

the current local air flow in the same process from the elbow to the vertical pipe. 

102 

VES017137 
Chapter 5 Kxperimental studies of particle dynamics by LDA 

Natural logarithm ofthe dimensionless particle number rate {ln(N/£(N))} 

4 0 , - - 40 

-40 ; -40 ' ' 

4 0 . -50 0 50 

Figure 5.22 Development of cross-sectional distributions of the dimensionless particle number 

rate jN/X(N)} of the third type of glass beads (180~300p.ni) under an air conveying velocity 

U,=10m/s and the solid mass loading ratio 1.9% in the vertical pipe behind an elbow (R/D=1.3) 

103 
An investigation ofparticle dynamics in a dilute phase pneumatic conveying system 

5.5 DISCUSSION AND COMPARISON 

5.5.1 The discrepancy between air velocity and particle velocity in the horizontal pipe 

David Mills (2004b) stated that the particle velocity would typically be about 80% of the air 

conveying velocity in a horizontal pipeline in dilute phase conveying and about 70% in vertical 

upward flow in a pipeline, which can be expressed in terms of a slip ratio of particle velocity over 

air conveying velocity. This statement is based on the concept that particle velocity should be 

lower than that o f the conveying air, since the mechanism of conveying is one of drag force in 

dilute phase conveying. However, he did not describe the related methods for particle velocity 

measurement or experimental data. 

0.6 j 

0.4 

0.2 

0 

-0.2 

-0.4 

-0.6 

0.6 

Smoke, mean U IU =1.1 

px a 

First, mean U IU =1.1 

px a 

Second, mean U III =1.2 

px a 

Third, mean U / U =1.3 

px a 

Ideal air, mean U /U =1.0 

0.7 0.8 0.9 

U /U 

px a 

1.1 1.2 1.3 1.4 

Figure 5.23 The vertical profile of axial mean velocity for four types of particles at the section 

ID in the horizontal pipe (Ua=10m/s, air conveying velocity; First: glass beads less than 50pm; 

Second: glass beads within 70—110 urn; Third: glass beads within 180-300 pm). 

So far, most cited experimental data of particle velocity in horizontal pipes are expressed as a 

one-dimensional profile along the gravity force direction (y axis). In order to make a convenient 

comparison with other related work, we re-plotted the experimental data on the horizontal section 

ID for three types of glass beads as well as smoke in the one-dimensional profiles shown in 

Figure 5.23. Compared with the one-seventh power profile of ideal turbulent flow (Rober et al., 

2004), we can obviously see that both profiles of smoke and the first type of glass beads have a 

good agreement with that of ideal gas flow and they are nearly identical only with minor 

104 
Chapter S l.xperimenlnl studies ofparticl e dynamics by LDA 

discrepancies, since both the first type of glass beads (<50pm) and smoke particles have a small 

Stokes number (<3.6) which gives a good ability to follow the flow of the transporting air. By 

contrast, the profiles of the second (70-1 10pm) and the third (I80~300p.m) types of glass beads 

show a significant discrepancy. The mean value of U p,/U a, is 1.1, 1.1, 1.2 and 1.3 for smoke, the 

first, the second and the third types of glass beads respectively. This indicates that the mean axial 

particle velocity of particles with larger size is greater than that of the smaller particles, which 

must result from high inertia of the larger particles. Since the empirical one-seventh power law 

states that the ratio of the average velocity to the centreline velocity varies from 0.79 to 0.87 in a 

fully developed flow in a smooth pipe, this means that fluid velocity at the pipe centre is about 

1.3 or 1.2 limes larger than the mean velocity. Consequently, particles with high inertia would 

retain their original velocities when accelerated in the fastest region of fluid or due to 

particle-particle collisions. We can in fact see that the axial particle velocities for the second and 

third types of glass beads are faster than that of air phase at a local point, especially in the region 

close to the pipe wall. In addition, we also notice that the maximum ratio of the axial particle 

velocity to air conveying velocity measures about 1.4, which is larger than that of 1.3 estimated 

by the one-seventh power law. The possible reason may be the kinematic energy of air flow 

increased due to turbulent energy lessened by larger micro-particles like the third type of glass 

beads. 

c=2.5 

10.00 15.00 20.00 25.00 30.00 tO.OO 15.00 20.00 25.00 30.00 10.00 15.00 20.00 25.00 30.00 35.00 

Fig. 7. Development of vertical profiles of particle phase properties along a horizontal glass pipe for different panicle mass loadings 

l(i=(0) 0.3, (O) 0.5 and (•) 0.7, superficial gas velocity (j',-23 m/s). (a) Particle concentration in kg/m!; (b) axial mean particle 

velocity in m/s: ic) axial particle velocity fluctuation in m/s; (d) number mean particle diameter in 

Figure 5.24 Experimental data of Huber and Sommerfeld (1994) for flow in a horizontal pipe by Phase 

Doppler Anemometry under air conveying velocitj' 23m/s for glass beads with a mean size 40pm 

With regard to particle velocity measurements in a horizontal pipe, Figure 5.24 shows the 

experimental data of Huber and Sommerfeld (1994) using Phase Doppler Anemometry (PDA). 

Apparently, the maximum particle velocity is about 30m/s, which is 1.3 times faster than the air 

conveying velocity 23m/s. They did not give any explanation. Then Kussin and Sommerfeld 

(2002) published their experimental data obtained by measuring the particle velocity of glass 

beads with mean size 100pm in a horizontal channel using PDA , as shown in Figure 5.25. Here, 

105 

VES017140 
A n investigatio n ofparticl e dynamic s in a dilut e phas e pneumati c conveyin g system 

particle velocity is clearly slower than air velocity except for the boundary region and the 

maximum ratio ofparticle velocity to air conveying velocity is about 1.0. 

1 O n 

0.4 

0.0 

0.5 1 2 

Fie.. 6a-c. Vertica l profiles lor air and 100-um particles with 

f' a v=I9.7 ni/s fer the low roughness case (Rl): a horizontal mean 

velocities of air atid particles; b horizontal component of nils velocity 

fluctuation; c vertical component of rms velocity fluctuation [open 

symbols*, air; closed symbols: particles) 

Figure 5.25 The experimental data obtained by Kussin and Sommerfeld (2002) 

in the horizontal channel using PDA. 

Figure 5.26 shows the experimental data of Tsuji et al. (1982) for flow in a horizontal pipe under 

an air conveying velocity of 15m/s and at different solid loading ratios. They extended the 

standard technique of LD A to measure simultaneously the velocities of air phase and solid phase 

by discerning the amplitudes of Doppler Signals scattered by the particles (plastic pellets with 

mean size 200pm and density 1000 kg/m3) and the seeding particles (ammonium chloride with 

mean size 0.6pm). Their experimental data show that the profiles ofparticle velocity are close to 

those of the air phase at the different solid loading ratios. The values of particle horizontal 

velocity to air conveying velocity are less than 1.3. 

F igur e It. Mean velocity distributions of air and 0 2 mm particles; 

(o) ".» . = 6 m/s; (t) 10 m/s; (c) 15m/« . 

Figure 5.26 Tsuji's experimental data (1982) by LD A in a horizontal pipe 

106 

VES017141 
Chapter 5 l-Aperimental studies of particle dynamics by LDA 

Figure 5.27 shows one set of the experimental data measured by Yilma z and Levy (2001) who 

used a libre-optic probe to measure time-averaged local particle velocities, concentrations and 

mass lluxes for pulverised-coal particles (90% less than 75pm) in a horizontal pipe. Their 

experimental data show that the maximum ratio of particle velocity to air conveying velocity is 

less than 1.2. 

According to the experimental data in the figures of 5.15, 5.16, 5.17 and 5.18, the previous 

experiments of measuring particle velocity in a horizontal pipe mainly focused on a single type of 

particle with varying different air conveying velocities or changing solid loading ratios. Under 

the same fluid conditions, experiments using the same materials with different sizes like our 

experiments are still scarce. 

10 

Top 

D = 0.154m 

U„ = 20 m/s 

• 

— - 1.00 

0.50 

» 0.33 

il f 

-

/ 

Bottom 

0,0 0.5 1,0 1.5 

Fig, + Effect of solids loading ratio (fiY (a) panicle velocity profiles 

Figure 5.27 Experimental data of Yilmaz and Levy (2001), obtained by using Optical-Fibre velocinictry 

107 

VES017142 
An investigation ofparticle dynamics in a dilute phase pneumatic conveying system 

5.5.2 Particle dynamics in the vertical pipe downstream of a right angle elbow 

On the section OD, z=0 

1 

ro 

3 

j 

CL j 

=> 0.5! 

1 O.l 

First 

Second 

Third 

: i I 

0.6 0.4 0.2 0 -0.2 -0.4 -0.6 -0.8 -1 

x/R 

_ 1500= 

•o I 

C ! 

o ] 

§ 1000; 

is I 

| r soo 

O L — i '.. ^ .... 

1 0.8 0.6 0.4 0.2 0 -0.2 -0.4 -0.6 -0.8 -1 

x/R 

Figure 5.28 Profiles of the axial particle velocity {Up ,) and particle number rate jNJ along the x axis on 

the section 0D in the vertical pipe downstream of the right angled elbow. (U„=10m/s, air conveying velocity; 

First: glass beads of size less than 50pm; Second: glass beads within the size range 70-110 pm; Third: glass 

beads within the size range 180-300 pm; R: pipe radius 37.5mm). 

In order to compare with the previous works, Figure 5.28 shows profiles ofth e axial particle 

velocity and particle number rate for three type of glass beads along x axis (z^0) from the section 

0D of the vertical pipe. The profile data of {U p y [ were extracted from Figure 5.14, Figure 5.17 

and Figure 5.20. The profile data o f {N} were obtained from Figure 5.16, Figure 5.19 and Figure 

5.22. Here the x positive axis points to the pipe outer wall. The section 0D is about 15mm away 

from the elbow outlet. 

Compared with contours o f !U p y / U u } and {ln(N/I(N))| in Figure 5.14 to Figure 5.22, the 

{Upy{profile does not illustrate the horseshoe-shaped feature in cross-sectional distribution on 

the section OD for three kinds of glass beads. But the profile of each {U p y } shows the decreasing 

tendency from the pipe outer wall to the inner wall (along the x negative axis), which is similar to 

that observed in the corresponding cross-sectional distributions. In addition, the axial particle 

velocity of the third type of glass beads is larger than that of the other two types, which indicates 

the inertial effect on particle velocity, since particles with high inertia should keep their initial 

108 

VES017143 
C'haplcr 5 Hxperimenlal .studies of panicle dynamics by LDA 

velocities rather than easily follow the carrier fluid. As for the profiles of particle number rate 

{N ]. the profile of the second type of glass beads reveals that the dust rope formed in the bend is 

close to the pipe outer wall. But we can not clearly see the rope from the profiles of the first and 

third types of glass beads. However, the regions with a high density of particles ofth e first and 

third types can be observed on their cross-sectional distributions of {N}. 

So far, three previous papers which experimentally study particle dynamics in a vertical pipe 

behind a pipe bend have been searched. Figure 5.29 shows the profiles of the axial particle 

velocity and particle concentration at the position 0.1m away from the elbow outlet. These data 

were measured by Huber and Sommerfeld (1994) who used PD A to study the degree of 

segregation of glass beads with mean size 40pm under 14 and 21m/s air conveying velocity with 

solid loading ratio 0.5 in a vertical pipe behind an elbow. Here the pipe outer wall locates at 

z=0mm. Their experimental data of particle concentration profile display the rope located at the 

region close to the pipe outer wall and the minimum velocity at the pipe outer wall corresponds 

to the velocity of the dust rope sliding along the wall. They thought it might be caused by 

momentum losses from particle-wall and inter-particle collisions. However this is different from 

that observed in Figure 5.12, which shows that particles within the rope region not only have the 

maximum particle number rate but also have the higher velocities. The region with the maximum 

axial particle velocity locates at the inside of the horseshoe shape of the cross-sectional 

distribution of {U p y } on the section OD. This feature is also observed in both Figure 3.20 and 

3.21 for air phase experimental data and numerical results. Moreover, glass beads with mean size 

40pm or less than 50pm have a low Stokes Number, which indicates that their profiles should 

show the features of the air phase. 

30.00 20.00 

20.00 40.00 80.00 SO.i 

t ta mm 

.00 

i in mm 

(£/,-(0 ) U m/s and (A ) 21 m/s) bend radius of R/D-25* 

stainless steel pipe, particle mass loading -0.5 

Figure 5.29 Profiles of the axial particle velocity and particle mass concentration 

(Huber and Sommerfeld, 1994) 

109 

VES017144 
A ll investigation of particle dynamics in a dilute phase pneumatic conveying system 

Another two experiments were performed by Yilmaz and Levy (1998, 2001). They used a 

fibre-optic probe to measure lime-averaged local particle velocities, concentration and mass 

fluxes over cross-sections in a vertical pneumatic conveying line following a 

horizontal-to-vertical elbow under a range of conveying air velocities and solids mass loadings. 

In their experiments, pulverized coal with mean diameter 75pm and true density 1680 kg/m3 

were conveyed with solid loading ratio 0.33 to 1 under air velocities from 15 to 30m/s. Since 

their latest experimental data in 2001 included the old results, Figure 5.30 shows their 

measurement results at the position close to the elbow outlet (z/D=l). Compared with Ruber's 

data in Figure 5.29, the profiles of particle concentration in Figure 5.30 show a high particle mass 

concentration close to the outer wall (along the x negative axis) for four different fluid conditions. 

Obviously, this finding is close to our experimental dala ofparticle number rate shown in Figure 

5.19. But the profiles of the axial particle velocities are only limited within a short distance x/D 

less than 0.3 and there is no data for the left space. The authors did not present any reason for 

this. 

Figure 5.30 Profile of the axial particle velocity and particle concentration at the position of 

z/D=l under different fluid conditions (Yilmaz andLevy, 2001) 

5.6 SUMMARY AND CONCLUSIONS 

Pneumatic conveying of granular materials is one of the most important applications in many 

industries. It is essenlial and necessary to characterize particle dynamics in different components 

110 

VES017145 
Chapter 5 Experimental studies of particle dynamics by LDA 

of a pipeline to explore the mechanism of pneumatic transport. In this chapter, the extended LD A 

technique discussed in Chapter 3 was applied to study cross-sectional features of three types of 

glass beads in a horizontal pipe and in a vertical pipe behind an elbow. 

In the horizontal pipe, the experimental data show that the cross-sectional flow patterns of the 

solid phase in the gas-solid pipe flow (glass beads less than 110pm) can be classified by annular 

flow describing the axial particle velocity contours and stratified flow characterising particle 

number rate distribution over a cross-section. However the position of the annular core and the 

values of iso-lines are dependent on particle size and vary along the fluid streamwise direction. 

By contrast, these two flow patterns can be still observed for the third type of glass beads 

(180~300p.m), but their characteristics are not clear like those for the other two types of glass 

beads, 

In the vertical pipe after an elbow (R/D=1.3), a horseshoe shape feature has been found on 

cross-sectional distributions ofthe axial particle velocity for all three types of glass beads on the 

section OD close to the elbow outlet. At the further downstream sections, the horseshoe-shaped 

feature is gradually distorted until it completely disappears. The distance for total disintegration 

is about 4D for the first type of glass beads, 2D for the second type and ID for the third one. As 

for particle number rate, its cross-sectional distribution on the section OD shows that a rope is 

formed at the pipe outer wall where the maximum particle number rate occurs. On the whole, the 

rope formed by the first type of glass beads can be still observed at the section 6D. For the 

second type of glass beads, the rope will disintegrate from the section 4D according to the 

similarities between cross-sectional distributions of {UP y/Ua } and {ln(N/£(N))}. Overall, the 

roping characteristic is not obviously shown in the gas-solid flow ofthe third type of glass beads 

after the section OD. All of these indicate that ropes formed from larger particles disperse more 

easily, for reasons perhaps related to their higher inertia. 

Moreover, the current experimental data have been compared with several previous experimental 

publications. These comparisons reveal that there exists much discrepancy between them. This 

discrepancy may be caused by possible factors of different instruments and different fluid 

conditions as well as different experimental rigs. Consequently, further experimental studies will 

be necessary to measure more granular materials under a range of fluid conditions for 

understanding the mechanism of pneumatic conveying. 

I l l 

VES017146 
Chapter 6 

Visualization and Measurement of 

Cross-sectional Characteristics of Solid Phase 

in a Dilute Pneumatic Conveying System 

In applications of dilute pneumatic conveying, the two important parameters ofparticle diameter 

and solid volume fraction have been intensively studied in numerous experiments and numerical 

simulations. But local information on their spatial distribution in pipes has scarcely been 

reported to date, especially over horizontal pipe cross-sections. This chapter presents a video & 

image processing method of measuring particle diameter and solid volume fraction through 

analyzing particle tracks and positions in frames of a video. Using a high definition camcorder, 

the behaviour qf the solid phase is recorded when particles cross a pipe cross-section which is 

highlighted by a light sheet produced by a halogen lamp. On every frame in a video, the 

instantaneous particle positions, particle diameter and the local solid fraction over the pipe cross 

section can be extracted. The corresponding time-averaged values can also be calculated 

through averaging data on all frames in a specific interval. The experimental results suggest that 

the gas-solid flow in a dilute pneumatic conveying system is always heterogeneous and unsteady. 

The parameter of particle mass mean size is superior to particle number mean size for 

statistically describing the unsteady properties ofgas-solid pipe flow. 

6.1 INTRODUCTION 

Pneumatic conveying systems are widely applied to process granular materials in many industrial 

fields. A pneumatic conveying pipeline system typically consists of horizontal and vertical 

sections as well as connecting elbows. Consequently, there exist different physical phenomena in 

different parts of a pipe line. For example, gravity settling occurs in horizontal pipes. Roping 

happens in an elbow due to a centrifugal force which makes particles concentrate into a rope. 

Obviously, gas-solid pipe flow is so complicated that understanding of its mechanism is still 

under development. Many features have still to be investigated, especially local information on 

solid phase velocity and particle diameter and frequency distribution over the pipe cross-section. 

These parameters are important in the design of systems to ensure even solid distribution 

between a main duct and the branches into which it divides. For example, in Co-firing 
An investigation of particle dynamics in a dilute phase pneumatic conveying system 

applications, estimating the spatial distributions of pulverized coal and biomass granular before a 

splitter is an essential step in determining how to split mixed fuel in a common transportation 

pipeline. 

In Chapters 3, 4 and 5, we extended the current Laser Doppler Anemometry (LDA) technique for 

pipe flow measurement and used it to explore particle behaviour over a series of cross-sections 

along the horizontal pipe. The experimental results demonstrated two kinds of cross-sectional 

flow patterns: annular structure and a stratified configuration, described by particle velocity and 

particle number rate respectively. Since LD A is a mono-point instrument with a high sample rate, 

it only provides information at a single spatial point in a flow field. Consequently, the measured 

cross-sectional patterns of solid phase measurements represent particle time-averaged 

characteristics with the assumption that gas-solid pipe flow is steady in time. However, this 

assumption ignores flow phenomena dominated by spatial structure, which must be determined 

by measuring fluid parameters on a whole field simultaneously. It is a cumbersome task to 

measure a parameter over a whole field by using a point-wise instrument. In order to investigate 

simultaneous particle behaviour over a pipe cross-section, using a light-sheet technique with 

image processing is a good choice. This is a common flow visualization method. In this 

technique, a light beam (laser or other light source) is formed into a sheet using cylindrical lenses. 

This light sheet is used for sectioning and illuminating flow to form a planar measurement region 

where fluid characteristics can be extracted from analyzing videos or photos recorded by a CCD 

or camera. 

The aim of flow visualization is to make flow patterns visible by adding smoke, oil or fine 

particles to trace fluid motion. This kind of technique has had a long development history. For 

example, Reynolds demonstrated that pipe water flow could be classified as laminar or turbulent 

by its Reynolds Number. This result was deduced through observing the dye streak when some 

dye was injected into a pipe flow. Another well known experiment was conducted by Ludwig 

Prandtl, who investigated unsteady separated flows behind wings and other objects in a water 

tunnel by utilizing flow visualization techniques (Sabersky et al, 1999). However, results 

obtained by early flow visualization techniques were qualitative descriptions of the flow field 

rather than quantitative data such as flow velocity. With progress in the hardware of optics and 

electronics as well as novel theories or algorithms in fluid mechanics and signal processing over 

the past two decades, some traditional visualization techniques have been developed or are under 

development into newer advanced instruments like Particle Image Velocimetry (PIV), Particle 

Track Velocimetry (PTV) and Electrical Capacitance Tomography (ECT). which can be 

employed for quantitative measurement of complex instantaneous velocity fields not only in a 

113 

VES017148 
Chapter 6 - Visualization particle cross-sectional characteristics in a horizontal pipe 

single phase flow but also in multiphase flows (Dyakowski et al., 2000; Datta et al., 2007). 

In previous literature related to flow visualization applications in gas-solid pipe flow, Hesselink 

et al. (1998) reviewed the influence of digital computers on the classical methods of flow 

visualization. He thought that the most striking and promising of these techniques were optical 

tomography and gradient imaging, which allowed the interior of flows to be probed and 

visualized using line-of-sight techniques applied from different directions. On the other hand, 

sheet-illumination techniques provided powerful means to visualize the interior of flows. Particle 

tracking was an intuitively attractive method for making velocity measurements, but care should 

be exercised when attempting to determine derivative data. 

So far, developing and applying tomography techniques by using different image media, such as 

ultrasonic, nuclear magnetic resonance, y-ray/X-ray, electric capacitance/resistance, are still 

current topics in fluid measurement. As for ultrasonic tomography, Brown (1996) developed a 

laboratory device to identify the gas-solid flow mode in a pipe. His experimental results indicated 

that a measurement frequency in excess of 1 MHz and particle diameter greater than 1mm were 

necessary. Warsito et al. (1999) and Utomo et al. (2001) also used this technique for measuring 

the time-averaged cross-sectional distribution of gas and solid holdups in a slurry bubble column. 

A doughnut-shaped macroscopic flow scheme was observed to represent the cross-sectional 

distributions for the gas holdup. Particles mainly distributed to the centre of the doughnut in the 

column. Correspondingly, Dyakowski et al. (2000) overviewed the principle of electrical 

tomography methods and their applications for investigating, monitoring and controlling wet and 

dry granular conveying systems. Using electrical capacitance tomography (ECT), Rao (2001) 

investigated instantaneous and time-averaged concentration distributions of large particles over a 

pipe cross-section under different flow regimes. Even in homogeneous air flow, the contour of 

particle concentration is like a stratified flow. In his experiments, polyethylene particles (mean 

size 2.8mm with 1123 kg/m3 density) were transported in a 40.4mm PV C pipe by conveying air 

at 28.6m/s velocity. Laurent et al. (2002) proposed a direct approach to discriminating annular 

from stratified flow through analyzing capacitance data rather than processing the images 

recorded by ECT. Its general idea for flow pattern classification relied on finding geometrical 

properties in a frame corresponding to a set of capacitance measurements. Azzopardi et al. (2008) 

used a twin-plane ECT system to monitor the flow rate of pulverised coal (mass median diameter 

61pm) transported by air in 36.8mm diameter pipe. The experimental results indicated that there 

were two types of systematic fluctuations in the time series of mass flow rate and concentration 

and the cross-sectional distribution of solid showed that the coal was concentrated around the 

pipe wall. There are also many other papers investigating the influence of factors such as wall 

114 

VES017149 
An investigation ofparticle dynamics in a dilute phase pneumatic conveying system 

roughness, pipe diameter and solid mass loading on cross-sectional particle concentration profiles, 

which are summarized by Fokeer et al. (2005) and Fuchs et al. (2007) . Since reconstruction 

algorithms used for inverting a set of measured data to map material distribution inside a sensor 

are a group of nonlinear equations, results deduced from linear approximations to the nonlinear 

equations would result in poor accuracy. 

As well as tomographic techniques, there are also many studies of gas-solid pipe flow using 

digital imaging methods, which can be applied to directly extract information like particle 

diameter, particle concentration and their distribution from one or series of gas-solid flow images. 

Among these studies, Huber et al. (1994) introduced a laser-light sheet technique to measure 

particle concentration distribution over a whole pipe cross-section through analyzing the light 

intensities scattered by particles on images taken by CCD. Since the light sheet intersected the 

pipe at 45° with respect to the pipe axis, the experimental data were not over a right angled 

cross-section. Kadamibi et al. (1998) extended the Particle Imaging Velocimetry (PIV) technique 

for particle diameter measurement and studied the Gaussian distributed intensity variation across 

the depth of the light sheet and the optical depth of field. For a given PIV light sheet illumination 

setup, the point spread function of the optical system should be less than 10% of the imaged 

particle diameter. Additionally, it is essential to ensure an imaged particle occupies at least 3 

pixels to obtain an accurate size estimate. Similarly, Miyazaki et al. (1999) also used PIV to study 

particle motion (glass beads, 2.9~3.9mm) in gas-solid spiral flow in a horizontal tube and Li et 

al. (2000) investigated particle behaviour (polyvinyl chloride and polyethylene particles with 

mean size 3.13mm and 4.26mm respectively) in a horizontal dilute swirling pipe flow. His 

experimental results indicate that the particle concentration profiles exhibit symmetric 

distributions with respect to the pipe axis and a higher particle concentration appears near the 

wall in the acceleration region. Morimoto et al. (2003) proposed a tuft grid method combined 

with a image processing technique to visualize the characteristics of a pneumatic type ultra fine 

powder classifier. Caicedeo et al. (2003) studied bubble characteristics as function of the gas 

velocity in a rwo-diinensional fluidized bed by using digital image analysis. Cater et al. (2005) 

introduced a method of using low-cost CCD combined with an electrostatic velocity meter to 

measure particle diameter, size distribution and mass flow rate in a dilute pneumatic conveying 

system. The features of particle-wall collision and the bouncing of particle during pneumatic 

conveying in the dilute phase have been visually analyzed by means of digital image techniques 

(Sommerfeld et al. 1999; Vasquez et al. 2008). 

According to the above discussions, it is clear that only a few studies have been dedicated to 

measuring cross-sectional characteristics of the solid phase in gas-solid pipe flow, especially 

115 

VES017150 
Chapter 6 Visualization particle cross-sectional characteristics in a horizontal pipe 

Ihere is a lack of papers describing the measurement of particle spatial distribution of the solid 

phase over a whole pipe cross-section. In this chapter, a video & image processing method that 

instantaneously measures particle diameter and particle concentration over a horizontal pipe 

cross-section as well as the characteristics of their time-averaged values by using a high 

definition camcorder and a powerful halogen light box, is introduced. 

Figure 6.1 Sketches of experimental rig and optical arrangement for experiments 

6.2 EXPERIMENTAL SETU P AN D FLOW CONDITIONS 

Figure 6.1 sketches the experimental rig in which all the experiments were performed. I he 

pipeline of the apparatus includes a 4m long horizontal section connected to a 2m long vertical 

pipe through a horizontal-to-vertical elbow. One T-type piece was installed to connect a screw 

feeder with the pipeline. In order to lessen the effect of electrostatic charging, all pipe metal 

connectors are earthed. 

The air flow provided by a centrifugal fan varies from 5~42m/s. Under the condition of 10 m/s 

air conveying velocity, the maximum value of solid loading ratio is about 1.6% for glass beads 

(size within 180~300um, density 2550 kg/m3) injected by the screw feeder. The measurement 

116 
A n investigation ofparticl e dynamics in a dilute phase pneumatic conveying system 

region is located on a horizontal pipe cross-section 240mm upstream of the elbow's inlet or 

3.60m downstream from the screw feeder injection position. When gas-solid flow passes through 

this section, particles ofthe solid phase are illuminated using a sheet of light approximately 2mm 

thick produced by a 500w quartz halogen lamp box. The light rays are arranged to be 

perpendicular to the pipe axis with the sheet cutting across the pipe. Particles within the light 

sheet are imaged using a high definition JV C GZ-IID7 camcorder, which is mounted on a tripod 

to focus on the measurement region centre. The camcorder axis intersects the light sheet at about 

a 45° angle, which is depicted in the sub diagram of Figure 6.1. 

The JV C GZ-HD 7 is a tapeless camcorder and has the features o f 10x optical zoom, 1/5 inch 

C C D sensor, optical image stabilizer and 2.7 inch colour LC D It can record 25 high quality 

frames (1920x1080 pixels) per second. Its shutter speed varies from 1/2 to 1/400011' of a second 

and the aperture from f/1.8 to f/8.0. It has also a 60GB unit hard disk which can store five hours 

video at full high definition. The video is stored in extended MPEG- 2 transport stream files, 

commonly known as M2TS , which is defined as a TO D file extension in JV C GZ-HD7 . Here, 

MPE G stands for Moving Pictures Expert Group, the committee of industry which created the 

standard. Transport stream (M2TS) is a communication protocol for audio, video and data which 

is specified in MPEG-2 , and which makes extensive use of motion compensated prediction to 

eliminate redundancy. The most significant extension of MPEG- 2 over MPEG- 1 is an 

improvement in options within a picture that can be used to perform motion compensated 

prediction o f interlaced signals. MPEG- 1 treats each picture as a collection of samples from the 

same moment in time (known as frame-based coding). MPEG- 2 has modes in which the data can 

either be predicated using one motion vector to give an offset to a previous frame or two vectors 

giving offsets to two different fields (Digital T V Group, 2008). Therefore, using JV C GZ-IID7 

will obtain more raw video data with high spatial resolution. 

In this study, fl. 8 aperture and l/250s shutter speed was empirically selected for our experiments. 

When particles passed through the exposed area, a two-minute video of their behaviour was 

recorded for every flow condition. Instantaneous or time-averaged local information on particle 

diameter and particle concentration was extracted from these videos. In the following sections, 

we will discuss the related video & image processing algorithms and the experimental results. 

6.3 VIDEO & IMAGE PROCESSING SYSTE M 

Since data rate is one of the key parameters in transmitting a series of high definition frames, the 

format of Moving Picture Experts Group-II (MPEG2 ) is implemented to code the particle videos 

in the JV C GZ-H 7 camcorder. The procedure of data processing in this study will be divided into 

117 

VES017152 
Chapter o Visualization particle cross-sectional characteristics in a horizontal pipe 

two main routines of video decoding processing and image processing respectively, which are 

sketched in Figure 2. Once the experimental videos have been obtained, the first step is to decode 

(he MPEG 2 videos into Audio Video Interface (AVI) format (Clarke et al. 1995). A n AVI video 

consists of series of uncompressed bitmap frames (BM P images) in which the coordinate of a 

pixel is directly matched to the corresponding point in the measurement region. Then an 

individual frame or several consecutive frames in a video can be extracted for further image 

processing at the next stage. 

f 

D«rco>3jng 

mmi to J 

wm p 

padicle 

from isnagpes 

Labelling particles by number 

1 

Statistical processing 

T 

v 

Figure 6.2 Flow chart of video and image processing 

In general, all video & image algorithms used in this research are implemented using 

VES017153 
A n iiivcsiigalion o f panicle dynamics in a dilute phase pneumatic conveying system 

MATLAB7. 0 with Image Processing Toolbox, also incorporating some routines described in 

Nixon (2002). In the procedure of processing a single image, the first step is to determine the 

boundary or pipe wall so as to reduce the noise caused by the data outside the pipe, since the 

measurement region is only one part of a frame. Then much of the other unwanted noise can be 

filtered by subtracting a reference image, which is taken before injecting particles into the pipe. 

In this way, only the data within the boundary or inside the pipe is kept and the rest is set to be 

background. According to Otsu's method (1979), the greyscale image converted from an original 

true colour frame is changed into a binary image by implementing Otsu's operator. This produces 

a binary image (white particle regions on a black background) which contains particle 

information ready for sizing and counting. In order to identify every separate particle, each 

region of white pixels will be labeled with a different number. The number of pixels contained in 

each labeled region is equivalent to the projected track of a particle's motion in the measurement 

region over l/250s. 

6.3.1 Principle of decoding a MPEG-2 video 

Figure 6.3 Three types of pictures in a video stream (red colour arrow means bidirectional) 

The format of the high definition video recorded by JV C GZ-HD 7 conforms to MPEG- 2 high 

profile and is stored in extended MPEG- 2 transport stream files. JV C provides the software 

called Cyberline PowerDirector 5 NE , which is used to convert transport stream files to program 

stream files in standard MPEG- 2 format, which can be replayed and edited by using common 

algorithms for MPEG-2 . This is a popular coding and decoding standard for digital compression 

or decompression of audio and video signals. A MPEG- 2 video removes both spatial and 

temporal redundancies by using compression algorithms based on the Discrete Cosine Transform 

for motion estimation and compensation. There exist three kinds of frames in a MPEG- 2 video 

stream (as shown in Figure 6.3), which arc Intra-coded (I), Predicative-coded (P) and 

Bidirectionally predicated-coded (B) pictures. I-pictures are coded without reference to other 

pictures. This is periodically applied to provide access points where decoding can begin. 

P-pictures represent the difference between the current picture and the reference picture and are 

usually compressed for reducing video stream redundancy. In addition, B-pictures can use the 

previous and next I- or P-pictures for motion-compensation, and offer the highest degree of 

compression (Tudor, 1995). 

119 

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Chapter 6 Visualb.ation particle cross-sectional characteristics in a horizontal pipe 

In a MPKG- 2 video, its stream is organized as a Group of Pictures (GOP) which are composite of 

1-. P- and B-pictures. A typical l:P:B picture ratio in a GO P is 1:3:8, and a typical display order 

of GO P is: 

B , B 2 h B 4 B 5 Pr, B 7 B 8 P 9 B, 0 B u P, 2 

where the subscripts mean positions in the original video. The encoder reorders the pictures into 

the following sequence: 

I 3 B i B 2 P( l B 4 B 5 P 9 B 7 Bg P1 2 Bh i B1 1 

Under this configuration, if the decoder encounters a P-picture, its motion prediction is with 

respect to the previously decoded 1- or P-picture; if the decoder encounters a B-picture, its 

motion prediction is with respect to the previously two decoded I- or P-pictures. 

In an encoding process, each picture in a video stream is divided into 16x16 macrobiocks, which 

consist of a 2x2 array of blocks (each of which contains an 8x8 array of pixels). Macrobiocks 

specify colours using a luminance channel to represent saturation (colour intensity), and two 

chrominance channels to represent hue. A red, green and blue (RGB) signal can be equivalently 

expressed as luminance (Y) and chrominance (UV ) components. For a standard definition video, 

MPEG- 2 streams are encoded in the common sampling structure of 4:2:0, which means a 

macroblock using four blocks for the luminance channel and one block for each of the two 

chrominance channels. Each of the I-, P- and B-pictures are processed by a 2-dimensional 

Discrete Cosine Transform (DCT), which can separate a picture into parts with varying visual 

importance. The DCT coefficients are quantized to reduce the number of bits needed to represent 

them. The run-length encoder scans the DC T matrix in a zig-zag order to consolidate the zeros in 

the matrix. Finally, the output o f the run-length encoder, motion vector data, and other 

information, are Huffman coded to further reduce the average number of bits per data item. The 

compressed stream is sent to the output device (Drake et al. 2005). 

Correspondingly, the process of decoding a MPEG- 2 video is essentially performed using the 

inverse encoding process. The input stream is Huffman and run-length decoded, resulting in 

quantized Discrete Cosine Transform (DCT) matrices. From the coded video stream, it 

reconstructs the i-pictures. Then P- and B-pictures are reconstructed by using the corresponding 

I-pictures, additional coded data and motion vectors. As a result, each pixel in an uncompressed 

frame in a decoded MPEG- 2 video has a clear relationship with a spatial position. These 

uncompressed frames can be extracted from the AV I video file for further image processing. 

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A n investigation o f panicl e dynamics in a dilute phase pneumatic conveying system 

6.3.2 Strategy for processing large volume of uncompressed frames (AVI files) 

With the dramatic volume expansion of uncompressed frames in a video file, technology is 

needed to effectively extract or browse a specific segment in a short time. The first strategy is to 

eliminate audio infonnation for increasing video rate during decoding a MPEG- 2 video. The 

second strategy performed is to cut a thirty-seconds part in a two-minute video for each set of 

fluid conditions, which is carried out during converting a JV C TO D file into the standard 

MPEG- 2 video. The file size of a 30s MPEG- 2 video is usual about 90 Mbytes. Its corresponding 

decoding file size is about 900 Mbytes. Such a large volume uncompressed file would consume 

much time in being loaded into computer memory and being indexed by frame number or a 

specific time or interval. The third strategy is to split a thirty-second uncompressed AVI file into 

30 sub files kept in Matlab mat data format, which will benefit in quickly and conveniently 

loading a video data file for the imaging process. Each sub-file will only accommodate one 

second worth of data of 25 frames according to the JV C GZ-HD 7 recording rate of 25 frames per 

second. Thus, we will obtain about 750 frames with high definition (1920x1020 pixels) at each 

measurement section within thirty seconds. 

Frame(1) Framefi!) 

Frame® 

Figure 6.4 Four specific frames in an AVI video 

In these experiments, all measurements were conducted in the rig shown in Figure 6.1. Glass 

beads within the range 180-300 pm (manufacturer's specification) were conveyed in <|>75mm 

glass pipes by an air superficial velocity of lOm/s. Figure 6.4 shows four typical frames (5l h, 101'

1

, 

121 

VES017156 
Chapter 6 Visualization particle cross-sectional characteristics in a horizontal pipe 

15* and 20 n ) in a one-second video consisting of 25 frames on the pipe cross-section 3.70 m 

away from the feed position. Al l four frames clearly display the instantaneous spatial distribution 

of solid phase over the cross-section. Comparing the four frames with each other, we clearly 

observe that particle number is greater in the pipe lower half than in its upper half. This is the 

gravity settling phenomenon in horizontal pipes. However, there are still some particles in the 

pipe upper half, which indicates that the particles are in a state of dynamic suspension rather than 

irreversibly depositing on the pipe bottom after 3.70m (which would happen if they were simply 

settling under gravity.). Consequently, these pictures show the heterogeneous nature of solid 

phase flow over a pipe cross section. In addition, the total particle number is also observed to be 

apparently different from frame to frame. This denotes the unsteady characteristic of gas-solid 

flow in time over the pipe section. Al l of these qualitatively demonstrate the heterogeneous 

spatial and unsteady temporal nature of gas-solid pipe flow in a dilute pneumatic conveying 

system. In the next section, we wil l show the extraction of quantative information from these 

uncompressed frames. 

6.3.3 Particle diameter and spatial position measurement 

In the above section, we have discussed how to decode a MPEG- 2 video and obtain the 

corresponding uncompressed frames which are high definition pixel pictures. Each pixel in a 

frame is mapped to a spatial position on the pipe cross-section which is illuminated by the light 

sheet. Figure 6.4 shows four sample uncompressed frames in an AVI video. Before extracting 

particle information from these pictures, it would be better to manually determine the pipe inner 

surface edge which forms the boundary of measurement region. With regard to the cross-section 

on each frame of Figure 6.5, it is clear that the white colour curves which are highlighted by the 

light sheet are the pipe edges. Since we use a halogen light rather than a laser light source, there 

exists a small divergent angle for the light sheet, which results in two white curved segments 

rather than one continuous oval curve encircling the section boundary. In order to eliminate noise 

from outside the pipe, a boundary template is created manually through setting data as zero for 

each pixel outside the pipe and setting data as 1 for each pixel inside the pipe. In this way, an 

uncompressed frame like frame (1) in Figure 6.4 multiplied by the boundary template results in 

the picture as shown in Figure 6.5. Thus the measurement region of 850x950 pixels can be 

separated from the entire picture o f 1920x1080 pixels under the current optical arrangement in 

our experiments. Each frame in a video will be implemented by a logic AN D with the boundary 

template to obtain the data only within the measurement region box. 

122 

VES017157 
A n invcstigalion orpartici e dynamics in a dilute phase pneumatic conveying system 

Figure 6.5 The region of the pipe cross-section on a frame 

With respect to the sub image within the measurement region in Figure 6.5, i l is a true colour 

picture which is stored in MATLA B as a three dimensional array that defines red (R), green (G), 

and blue (B) colour components for each individual pixel. The colour of each pixel is determined 

by the combination of the red, green and blue intensities stored in each colour plane at the pixel's 

location. Observing particle images in Figure 6.5, we can see that particle images are much 

brighter and close to white. In contrast, the colour of the positions with no particle tends towards 

black. Therefore, it is convenient to separate particles from the background in the picture 

according to their luminance information rather than their colour data. The matrix of the colour 

picture in RG B space will be converted into the space of luminance (Y) and in-phase 

chrominance (I) as well as quadratic chrominance (Q) by using equalion (6.1) (Bovik Al , 2000). 

~Y~ "0.299 0.587 0.114 ~R~ 

I = 0.596 -0.27 5 -0.32 1 G (6. 

0.212 -0.52 3 0.311 B 

If all the components of the I and Q matrixes are set to zero while retaining the luminance matrix 

Y, the true colour sub-image will be converted to a greyscale one. Figure 6.6 shows the colour 

sub-image ofthe measurement region and its corresponding grayscale picture converted by using 

Equation (6.1). 

123 

VES017158 
ChaplL'r 6 Visualization particle cross-sectional characteristics in a horizontal pipe 

(a) color image (b) gray image 

Figure 6.6 Particle images on the pipe cross-section 

Since digital images are prone to a variety of types of noise due to electronic transmission or 

other processes, enhancement algorithms like the Wiener filter (Urn et al. 1990) have been used 

to reduce image noise and increase particle contrasts in the picture for facilitating the extraction 

o f particle information. The Wiener filter is an adaptive filter which uses a pixelwise adaptive 

method based on statistics estimated from a local neighbourhood of each pixel. Its algorithm can 

be described as 

1 

M = 

NM 

1

 XX("i'"2)~v~ 

(6.2) 

NM 

where r\ is the N-by- M local neighbourhood of each pixel in the image A in which a is one 

element. Using the estimates of equation (6.3), a pixelwise Wiener filter can be created. 

{nl,n2) = fi + -

o~ —v 

a' 

(a(n^n 2 )-/j ) (6.3) 

where v" is the noise variance. Its value is calculated from averaging all the local estimated 

variances in a frame. Figure 6.7 (a) shows the results of the gray image in Figure 6.6(b) 

denoised by a Wiener filter. 

Observing the raw images in Figure 6.6 as well as the denoised image and Figure 6.7(a), we still 

notice that the background of each image is heterogeneous and is divided into a three striped 

124 

VES017159 
A n investigation ol" particle dynamics in a dilute phase pneumatic conveying system 

regions with different brightness. On the left and right side of the images, the brightness of the 

background is much higher than that in the field between two sides. This results from the optical 

arrangement for the measurement system in practice. Consequently, we must reduce the effect of 

an inhomogeneous background on converting a greyscale image to the binary one. In other words, 

the heterogeneous background should be separated from the particles in an image, which can be 

realized by using a Median Filter (Lim et al., 1990). The Median Filter is a nonlinear operation 

which is more effective than convolution for reducing "salt and pepper" noise while preserving 

edges. Since fine particles are pneumatically transported in the dilute phase, their images in a 

picture can be considered as some kind of noise like "salt and pepper". When an m-by-n 

Median Filter is performed on an image matrix in two dimensions, each output pixel contains the 

median value in the m-by-n neighborhood around the corresponding pixel in the input image 

(Nixon et al., 2002). As a result, Figure 6.7 (b) shows the corresponding result of processing the 

denoised image (Figure 6.7 (a)) by using a 25 x 25 Median Filter. Using this filter, we have 

obtained a separated background through removing particle images in fhe denoised picture of 

Figure 6.7(a). It is clear that the separated background image still keeps its original features. 

(a) The denoised image (b) The separated background 

Figure 6.7 Denoising the image (a) and separating the background (b) 

Subsequently, when the denoised image of Figure 6.7 (a) has its separated background image 

Figure 6.7(b) separated, the subtraction residue is shown in Figure 6.8 (a) in which, while the 

heterogeneous background was removed, we have obtained most of particles with some segments 

ofthe pipe edge or the boundary of the cross-section. Since the noise resulting from shadows and 

1 2 5 
Chapter 6 Visualization particle cross-sectional characteristics in a horizontal pipe 

variant illumination in Figure 6.7 (a) has been eliminated through the above subtraction process, 

the entire image of Figure 6.8 (a) can be converted from a greyscale image to the binary one by 

using an optimal thresholding process. Otsu's method (Otsu, 1979) is one of the most popular 

techniques of optimal thresholding to automatically perform histogram shape-based image 

thresholding or reduce a greyscale image to the binary one. Essentially, this technique maximizes 

the likelihood that the threshold is selected so as to separate the image between an object and its 

background. This is achieved by choosing a threshold level that gives the best separation of 

classes, for all pixels in an image. The image to be thresholded is assumed to include two kinds 

of pixels which are classified as foreground and background respectively. Then it calculates the 

optimum threshold separating those two classes so that their combined spread (within-class 

variance) is minimal. Figure 6.8 (b) shows the corresponding binary image of Figure 6.8 (a) 

thresholded by Otsu's method. Comparing Figure 6.8 (b) with Figure 6.8 (a), we can see that 

particle images are highlighted in a homogeneous black background. 

(a) Eliminating the background (b) The binary image 

Figure 6.8 The image with its background subtracted (a) and its binary image (b) 

So far, the binary image as shown in Figure 6.8 (b) has been obtained and is suitable for applying 

quantification algorithms to extract essential particle features such as shape, size and spatial 

positions. Since a particle taken by CC D is represented as a collection o f bright pixels in an 

image, it can be classified by object descriptors which are used to describe the properties of the 

group of pixels forming a particle image. Two object descriptors of Region and Shape, which 

characterize the arrangement of pixels within the area and the configuration of pixels in the 

126 

VES017161 
An investigation of particle dynamics in a dilute phase pneumatic conveying system 

perimeter or boundary respectively, are used to describe an object. A region usually describes 

interior points which are surrounded by a boundary or perimeter which is also often called the 

region's contour or shape. A shape can be traced by quantifying the relative position of 

consecutive points on the boundary of a region. Thus, the key point for two descriptors lies in 

obtaining particle contour or shape. 

(a) Particle raw image (b) Connectivity in Chain Codes ( c) Particle scaled image 

Reference point: start (x, y) 

Chain codes = 

{4,3,4,2,2,2,3,4,2,3,4,2,2,2,3,4,2,2,2,3,4,0,2,0,6,6,7,0,6,7,0,6,6,7,0,6,6,6,7,0,6,6,6,6,6} 

Figure 6.9 Particle sample chain codes with 8-way connectivity template 

The method called the chain code technique, which stores the relative co-ordinates between 

consecutive pixels, achieves the shape of a region by analyzing each point on the boundary in 

sequence and assigning a code to denote the spatial direction between two adjacent points. For 

8-way connectivity, one pixel has eight possible relative relationships with its neighbors. The 

relationship template is shown in Figure 6.9 (b) where each number of 0-7 is encoded as one of 

the major compass directions. Given a complete border which is equivalent to knowing a set of 

connected points, if we define the first left-top point of a particle as the start position or the 

reference point, the chain code ofthe particle border is formed by concatenating the number that 

designates the direction of the next adjacent points along an anti-clockwise direction. That is, 

given a pixel, the successive direction from one pixel to the next pixel becomes an element in the 

final code. This is repeated for each point until the start point is reached again, when the shape is 

completely analyzed. For example, the image of a particle track taken by CC D in Figure 6.9 (a), 

which is inverted from Figure 6.8 (b), is enlarged for visualizing its pixel group as shown in 

Figure 6.9 (c). The particle's first pixel (Po) on the left top position is marked as "start" which 

is the reference point of encoding the particle border chain. According to the 8-way connectivity 

127 
Chapter 6 Visualization particle cross-sectionai characteristics in a horizontal pipe 

template shown in Figure 6.9 (b), the direction from the start point (P0 ) to the next (P|) is south 

(i.e. code 4) on an anti-clockwise loop, so the first element of the chain code describing the shape 

is 2 . Then the direction from point (P[) to the next anti-clockwise adjacent point (P2 ) is 

southeast (code 3), hitherto the next element of the code is 3. This coding is repeated until the 

44l h point (P44), which is connected westwards to the starting point (Po), so the last element (the 

4 5 t h clement) of the code is 6. Subsequently, the total area, perimeter and geometric centre 

bounded by the Chain Codes can be deduced. 

In Figure 6.9 (c), the group of black pixels forms the area ofthe sample particle trajectory within 

l/250s (CC D shutter speed) projected on the pipe cross-section. In order to simplify the question 

and avoid more complicated morphological analysis, the shape of a particle trajectory is an 

approximate rectangle whose area (S) is equal to the product of the trajectory length (L) and 

particle diameter (Dp ). It can be defined as 

S = LxDp (6.4) 

For example, the total area (S) ofth e particle trajectory in Figure 6.9 (c) is counted as 78 square 

pixels. If the coordinate of the start point is assumed as (0, 0) pixel, the point at the right bottom 

of particle trajectory locates at (17, 9) pixel. Thus the length of the particle trajectory is figured 

out by equation (6.5) 

L = V (l7-0) 2-(9-0) 2 * 19.24 (6.5) 

Thus, the particle diameter is equal to 

D

- % = %.2 4 =

 4 < 6

^ 

A n d the coordinate of the area locates at (17-0, 9-0)/2 = (9, 5) related to the start point. Then the 

local concentration of solid phase can be calculated too, which will be introduced in the next 

section for applying the above discussed algorithms for extracting particle features on a whole 

pipe cross-section. 

6.4 RESULTS & DISCUSSION 

The experiments were conducted over a pipe cross-section which was 240mm upstream of the 

elbow inlet or the 3.60m downstream of the particle injection position in the rig (shown in Figure 

6.1). Glass beads of size 180~300um and density 2550 kg/m3 (manufacturer's specification) were 

conveyed in <|>75mm glass pipes by an air superficial velocity of lOm/s. For each fluid condition, 

we actually recorded two minutes video in which 30s data were cut for particle image analysis. 

Therefore, a total number o f 25x30=750 frames will be used for extracting particle information, 

according to the sample rate of JV C GZ-HD 7 (25 frames per second). In section 6.3.2, we have 

128 

VES017163 
A n investigation ofparticl e dynamics in a dilute phase pneumatic conveying system 

displayed a group of four sample frames (5t h, 10t h, 1511' and 20t h frame) in Figure 6.4. These four 

frames were extracted from a one-second MPEG- 2 video which was also one thirtieth of the 

video data. Observing these four frames, we can clearly and directly see some qualitative features 

such as gravity settling, which results in a higher particle number density in the pipe lower half of 

the pipe and a more dilute suspension in the upper half. Moreover, particles are distributed over 

the whole pipe section rather than only in the pipe bottom, which indicates that the particles are 

in a state of dynamic suspension rather than irreversibly depositing on the pipe bottom due to 

gravity settling after running a 3.75 m distance from the particle feed position (which would 

happen i f the particles were simply settling under gravity). On the other hand, the total number of 

particles differs from frame to frame and the shape of the particle spatial distribution over a 

whole section is also different. These kinds of variation of particle distribution demonstrate the 

heterogeneous and unsteady characteristics of gas-solid pipe flow in a dilute pneumatic 

conveying system. 

50 

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60 

Mean diameter by number (pm) 

169 176 206 193 

0-100 

I Bi 

100-150 

I 1 111 

150-200 200-250 250-300 300-350 

Dp ( um) 

| 40 

20 

Mean diameter by mass (pm) 

285 279 288 283 

II . 

0-100 100-150 150-200 

I 

200-250 

II 

250-300 300-350 

Dp (pm) 

Figure 6.10 Particle diameter frequencies by number and by mass on four example frames 

With regard to particle quantitative properties over the whole cross-section. Figure 6.10 shows 

the measured diameter distribution (the normalized particle number vs. particle diameter and the 

normalized particle mass vs. particle diameter) in the four frames (5l h, 10*, 15l h and 20l h ) as 

shown in Figure 6.4. These results have been analyzed by using the algorithms of video & image 

129 

VES017164 
Otapler 6 Visualization particle cross-sectional characteristics in a horizontal pipe 

processing discussed in the previous sections. On the whole, we can observe that the shape of the 

particle diameter distribution curve is approximately conserved over the four example frames, 

and close to the specified particle distribution. But the frequency's absolute value at every size 

bin varies over the four frames. This denotes the instantaneous unsteady characteristic of 

gas-solid pipe flow at every moment. From particle diameter distribution by number, it is clear 

that particle diameter is mainly concentrated within two intervals of less than lOOum and 

175~200pm. Their number fractions are more than 20% and the number fractions in the other 

size intervals are less than 10%. In addition, the mean particle diameter by number on each frame 

is different within a standard deviation of 16.8pm from the set of particle mean size by number 

(169, 176, 206, 193) pm. On the contrary, there are three groups of particles whose mass 

fractions are more than 10%, as shown in Figure 6.10. Comparing these two diagrams, we can 

see that tine particles less than lOOum only occupy a small mass fraction less than 5%, although 

their quantity in terms of particle number is more than 20%. Considering particle mean size by 

mass on each frame, its measured set of (285, 279, 288, 282) jam shows a narrow variation, since 

the standard deviation of the set is only 3.9pm compared with that by particle number. It denotes 

an invariance of particle mean size by mass. 

The variations of two kinds of mean size in a second 

300 . , 

„ type mean std range . n , Jmhp r 

| 250 + 213.1 14.8 67.8 by number 

o 279.5 6.8 33.5 by mass 

200 

150

 1 ' 

0 100 200 300 400 500 600 700 800 900 1000 

time (ms) 

Figure 6.11 The variations ofparticle number mean size and particle mass mean size over Is 

In order to investigate the temporal variations of particle mean size by number and particle mean 

size by mass, their temporal variations within one second are plotted in Figure 6.11. A 

time-averaged value is calculated by averaging the corresponding data on all frames in the 

130 

VES017165 
A n investigation of panicl e dynamics in a dilute phase pneumatic conveying system 

specific interval. Obviously, the evolution of particle mean size by mass (the red curve) varies 

narrowly with a mean value of 279.5pm and a standard variance 6.8pm within a variation range 

of 33.5pm. Correspondingly, the evolution of particle mean size by number (the blue curve) 

varies widely with a mean value o f 213.1pm and a standard variance 14.8pm within a range of 

67.8pm. This is similar to the result shown in Figure 6.10. Therefore, the parameter of particle 

mass mean size, rather than particle number mean size, is statistically more consistent to describe 

the steady characteristics of particle diameter in unsteady gas-solid flow, since larger particles 

have larger weight factors than smaller ones when the mean mass flow rate is calculated over a 

pipe cross-section. Using particle mean size by mass rather than particle mean size by number is 

more suitable to describe the statistical properties of unsteady gas-solid flow over a cross-section. 

For this reason, the following results will focus on the time-averaged property of particle 

concentration and particle accumulation number (defined as the total number of particles counted 

in an interval) as well as their cross-sectional distributions. 

Figure 6.12 shows two kinds of cross-sectional distributions o f particle accumulation number and 

the normalized values of particle time-averaged concentration over the measurement section at Is 

and 30s separately, which are totally counted or time-averaged from the corresponding 25 frames 

and 750 frames respectively. In general, all of the four diagrams in Figure 6.12 not only clearly 

display the phenomenon of gravity setting but also show a stratified flow pattern layered by 

particle number or particle concentration over the cross section. But the contours over 30s show a 

relatively clear and uniform stratification structure, compared with that over 1 s, especially for the 

diagram of particle concentration distribution. This means that the distribution of particle number 

or particle concentration requires the averaging of more frames to produce good quality statistical 

features. 

In comparison of Figure 6.12 and Figure 6.13, which is the contour of the dimensionless particle 

number rate at the section 3D selected from Figure 5.12, both of them demonstrate a similar 

cross-sectional flow pattern resembling a stratification structure for the spatial distributions of 

particle number and particle concentration over the cross-section in a horizontal dilute gas-solid 

pipe flow. However, iso-lines in the two figures have different values and may be located in 

different positions, especially in the region close to the pipe top wall where the experimental data 

obtained by LD A still show the dimensionless {N/ln(Z(N)) with a larger value. 

131 
Chapler 6 Visiinli'/atuin particle cross-sectional characteristics in a horizontal pipe 

u.il I'.'j.imtm I.i Ih.i i tn.lit numhi'i (ln|N i.N)r

 in is Natural logarithm a. Uiq dirnsncirjnlcss particle number {ln(N/;;N)} in 3Ds 

, #• -l • -s 

X 

.1 * f . 

0.2 • & 

S o 

(a) Contours of the dimensionless particle number over Is and 30s 

UipiJimonsionloss particle ^on centra tion '>"(C IhedimenslonlesE particlo conconl/aJon |C l±(C )) (%| ovtir 30s 

(b) Contours of the dimensionless particle concentration {Cp/sumfC^)) over Is and 30s 

Figure 6.12 Cross-sectional distributions of the dimensionless particle counting number and the 

dimensionless particle concentration (N is the particle counting number; R is the pipe radius; {C,,} is 

the local concentration of solid phase) 

Natural logarithm of the dimensionless particle number rate {InlN/^N)} 

-4D -30 -20 -1 0 0 10 2 0 30 40 

z|mm) 

e \ X=-9, -8. -7. -6, -5,-4 Sections Total {N} (*10f) 

n x 10" 4,n=2.4 , 10.25,68,18- 3 3D 0 80 

.• J.j 

I 

Figure 6.13 The contdur of |ln(>J/Z(N)} on the section 3D measured by LD A (selected from Figure 5.12) 

132 

VES017167 
An investigation of particle dynamics in a dilute phase pneumatic conveying system 

6.5 SUMMARY AND CONCLUSIONS 

In this chapter, we developed a video & image processing system for measuring particle diameter 

and analyzing the spatial characteristics of particles over a horizontal pipe cross-section in a 

dilute pneumatic conveying system. A light sheet produced by a halogen lamp box was used to 

illuminate and cut a slice of gas-solid flow over a pipe cross-section. Then we used a high 

definition camcorder to record the particles' behaviour over the highlighted region. A set of video 

algorithms has been developed to decode the compressed MPEG-2 videos into the AVI format for 

further image processing. An AVI video, like a database, consists of a series of uncompressed 

frames. Each pixel on each uncompressed frame is directly mapped to a spatial point in the 

measurement region. Subsequently, the size and location of each particle can be extracted from 

every frame by using our developed image algorithms. 

As for image processing, firstly, each colour frame which is extracted from an uncompressed AVI 

video will be converted into the corresponding grey picture according particles luminance 

information; Second, it will be denoised by Wiener filter; The third step is that a background 

image will be obtained through removing particle images in the denoised picture by using a 25 x 

25 Median Filter. In this way, the feature of background environment can be kept. Subsequently, 

when the separated background image is subtracted from denoised image, the heterogeneous 

background will be able to be removed. Then this grey image is to be converted into a binary 

image by using Otsu's method. Finally, the features of every particle such as shape, size and 

spatial position can be extracted by applying the Chain Code Technique, which stores the relative 

co-ordinates between consecutive pixels, achieves the shape of a region by analyzing each point 

on the boundary in sequence and assigns a code to denote the spatial direction between two 

adjacent points. Then particle diameter distribution and mean size over a section can be 

calculated from the set of Chain Code. 

The experimental results of particle diameter and size distribution on each frame suggest that 

gas-solid pipe flow is always heterogeneous in space and unsteady in time. According to their 

fluctuations in temporal space, using particle mean size by mass is more suitable to statistically 

describe the unsteady properties of gas-solid pipe flow. On the other hand, both the contours of 

particle accumulation number and particle time-averaged concentration exhibit a flow pattern 

resembling a stratified structure over a horizontal pipe cross-section in gas-solid flow. This kind 

of stratified structure is similar to the results explored by the experimental data of Laser Doppler 

Anemometry in Chapter 5. But iso-lines may have different values and be located in different 

positions. 

133 
Chapter 6 - Visualization particle cross-sectional characteristics in a horizontal pipe 

Needless to say, the current developed video & image processing system can be used to 

measure the size and spatial distribution of particles more than 80um over a whole 

cross-section in <t>75mm pipe. Thus, this visualization system will be suitable for fine 

particles measurement by using a smaller size of pipeline for experiments. In addition, using 

coloured granular materials, this system can be developed into a measurement tool for 

gas-solid pipe flow with a multi-component solid phase by adding the function of discerning 

particle colour. 

134 

VES017169 
Chapter 7 

CFD Investigation of Cross-sectional 

Flow Patterns of Solid phase in 

Gas-Solid Granular Pipe Flow 

This chapter presents numerical predictions of flow patterns on cross-sections along a 

horizontal pipe using the Discrete Phase Model (DPM) of Fluent 6.3.26 as well as the latter 

coupled with the Discrete Element Method (DEM) software of EDEM 1.3.1. The simulations 

are compared to experimental measurements on glass beads (size 70-110pm, solid loading 

ratio 1.6%) transported by 12m/sairin $75mm glass pipes. Using Laser Doppler Anemometry 

(LDA), the measured contours of the horizontal particle velocity component show an annular 

structure over the pipe cross-sections; this flow pattern can also be described as stratified 

flow over cross-sections, layered by particle number distribution. The comparisons of 

numerical and experimental cross-sectional flow patterns of solid phase show that there is 

reasonable agreement at pipe cross-sections located at horizontal positions less than half the 

product of particle mean velocity and mean free fall time in the pipe from the particle inlet. 

Further away from the inlet, the numerical results show flow patterns which are increasingly 

divergent from the experimental results along the pipe in the direction of flow. This 

discrepancy indicates that particles'spatial distribution in a pipe is not accurately predicted by 

DPM or Fluent coupled with DEM. Moreover, it is necessary to validate and develop 

numerical models by using the latest experimental data. 

7.1 INTRODUCTION 

In Chapter 2, the effects of some macro parameters like the Saffman force and Stokes number on 

pneumatic transportation have been investigated using the Discrete Phase Model (DPM) in 

Fluent 6.2.16. In Chapters 4-6, we presented experimental results of solid phase distributions 

over a series of cross-sections in the horizontal pipe by using an extended Laser Doppler 
An investigation of particle dynamics in a dilute phase pneumatic conveying system 

Anemometry (LDA) technique and developing a visualization system involving video recording 

and Image processing. These experimental results display two cross-sectional flow patterns ofthe 

solid phase, resembling an annular structure and stratification in a horizontal pipe. The annular 

structure represents the contour of particle velocity and the stratified image represents the contour 

of particle number rate over a pipe cross-section. These experimental data provide a good tool to 

validate the availability and limitations of the current numerical models for pneumatic conveying 

research. 

Generally, flow regimes for horizontal conveying of granular materials can be classified into 

dilute suspension flow, stratified flow, sedimentation dune flow, plug flow and moving bed flow 

(FAN, 1998). These flow regimes are usually observed along the pipe axis and each is a 

qualitative term depicting the macro-state of gas-solid flow. 

So far, research into solid phase distribution over a pipe cross-section is still scarce. Most 

numerical and experimental studies only show one-dimensional local information on the solid 

phase along a line rather than two-dimensional data over a whole cross section. Among these 

studies, the experimental work of Tsjui (1983), used Laser Doppler Velocimetry to measure the 

velocity of mixed plastic particles, size 200pm and 3.2mm, density 1000kg/m3; conveyed by air 

of velocity 6,10 and 15m/s in a 30.5mm diameter horizontal glass pipe. The vertical profile of the 

normalized axial particle velocity became flattened with increasing particle size or solid loading 

ratio, and the profile peak was shifted upwards above the pipe centre line. This is also confirmed 

by Huber's (1994) experimental data (glass particle size 40pm; air velocity 21 m/s and (|)80mm 

glass pipe). Huber not only used Phase Doppler Anemometry (PDA) to measure the particle 

velocity profile, but also applied the light-sheet method to measure particle concentration over 

the pipe cross-section through analyzing the light densities scattered by particles in images taken 

by CCD. The contours of particle concentration over pipe cross-sections clearly display an 

annular structure, but their core regions were located in the lower half of the pipe due to 

gravitational settling. Using Electrical Capacitance Tomography (ECT), Rao (2001) measured 

solid phase concentrations over a whole pipe cross-section in various flow regimes. The 

experimental system was a r{)40.4mm PV C pipe in which air at superficial velocity 10.4 

~28.6m/s transported three large particle types, which were titanium dioxide (3.01mm, 

1683kg/m3), brown mustard (1.76mm, 879kg/m3) and polypropylene (2.8mm, 1123 kg/m3). In 

the homogeneous flow regime, the contour of time-averaged particle concentration 

(polypropylene, air velocity 28.6m/s) showed a stratified structure over the cross-section. 

Due to the complexity of gas-solid pipe flow, particle transportation is still an area of keen 

interest in computational fluid dynamics studies. Most numerical simulations in this field have 

136 

VES017171 
Chapter 7 CFD investigation of cross-sectional flow pattern of solid phase in a horizontal pipe 

been performed using the Euler/Lagrange approach, which has been developed into the standard 

Discrete Phase Model (DPM) in the commercial Computational Fluid Dynamics (CFD) software 

package FLUENT. Among numerical studies of solid phase spatial distribution in horizontal 

pipes, Huber's (1998) numerical results show that 40pm glass particles have a good ability to 

follow the fluid in air of 24m/s superficial velocity in a <J>80mm smooth glass pipe and that their 

trajectories are distributed over the whole pipe space. Further, Sommerfeld (2003) investigated 

the effect of wall roughness on trajectories of 30~700pm particles transported by 18m/s air in a 

2D channel with 6m length and 35mm height. The calculated trajectories of 110pm particles 

without considering the effect of wall roughness indicated that all of them were concentrated in 

the channel bottom region after 3m forward progress, although they were homogenously injected 

at the inlet. Although there are some papers on the study of solid phase distribution over 

cross-sections of pipe bends and vertical pipe runs, their results are not discussed here since it 

was decided that horizontal pipes provide the best test of the predictions ofthe two methods. 

In the following sections, the numerical models and the corresponding parameters will be 

introduced firstly. Then the experimental data, which have been measured by the extended 

technique of Laser Doppler Anemometry, will be summarized. The experimental results include 

contours of particle velocity and particle number rate on a series of horizontal pipe cross-sections. 

Basing the inlet condition of numerical simulations on the actual experimental data, theoretical 

predictions of flow patterns on pipe cross-sections have been explored by using the DPM option 

of Fluent and Fluent coupled with EDE M respectively. Then we discuss the limitations of current 

numerical models through analyzing the discrepancy between numerical results and the 

corresponding experimental data. 

7.2 NUMERICAL MODELS AND THEIR PARAMETERS 

7.2.1 Mathematical models 

In dilute pneumatic conveying, the forces acting on particles may be classified into three groups: 

(1) forces due to the interface between fluid and particles, (2) forces due to the interactions 

between particles and collisions of particles with the wall, and (3), forces imposed by external 

fields such as gravity (Fan, 1998). The forces in the first group normally are the drag force, the 

Saffman lift force, the thermophoretic force, the Magnus force, the Brownian Force and a force 

related to the pressure gradient. The forces in the second group are accounted for in the 

particle-wall collision model and particle-particle interaction models. In the standard DPM of 

Fluent, which has been introduced in Chapter 2, the standard particle motion equation does not 

include items corresponding to the Magnus force and the force related to the pressure gradient. It 

also ignores particle-particle interactions so as to reduce the expense of computation. The 

137 

VES017172 
An investigation of particle dynamics in a dilute phase pneumatic conveying system 

concept of parcels, which represents a group of particles with the same properties such as particle 

size, density and injection position, is introduced in DPM. Thus, DPM in Fluent is modelled to 

track a set of parcels or particle stream rather than each individual particle in the domain. 

An alternative approach different from DPM has been introduced to develop two-fluid continuum 

models that consider the gas and solid phases as two interpenetrating continua. Then the 

mechanical behaviour of the solid phase is described by the discrete element method (DEM) and 

air phase flow structure is solved using the traditional CFD method. Basically, this approach is a 

coupled DEM-CFD calculation. In the coupled DEM-CFD calculations, conservation equations 

for the solid phase are no longer required in CFD calculations using the commercial software 

Fluent. The DE M model directly calculates the solid phase terms in the air phase equations, such 

as the momentum exchange coefficient between the phases and the mean solid phase velocity. 

Tracking the motion of individual particles allows a precise calculation of how the solid volume 

associated with these particles changes with time. 

In order to investigate the actual particle-particle influences, Crapper et al. (2005) used a coupled 

simulation using DE M together with FLUEN T to study particle characteristics in elbows of a 

dilute pneumatic conveying system, since there exist in bends many strong particle interactions. 

Similarly, Yu et al. (2005) also used the discrete element method coupled with computational 

fluid dynamics to study the pneumatic transport of polypropylene beads (maximum number 2000, 

diameter 2.8mm) in both vertical and horizontal one metre long pipes. Their numerical results 

only focused on solid phase flow along the pipe axis under different operating conditions. Several 

research workers have applied the method of combining DE M with CFD to simulate plug flow 

and fluidized beds (Tsuji et al. 1992; Tsuji et al. 1993; Rhodes et al. 2001). Here, we use the 

commercial DE M software called EDE M which was developed by DE M Solutions Limited of 

Edinburgh. It can be directly coupled with Fluent for the simulation and analysis of granular 

material handling and manufacturing operations (Dem-solutions, 2008). 

Since both DPM and DE M have been developed to be standard models in commercial software, 

the detailed equations governing the phase dynamics will not be replicated here. We only focus 

on selecting the suitable model parameters. Table 7.1 and 7.2 list all the numerical parameters 

used here for DPM and DEM-Fluent simulations respectively. 

138 

VES017173 
Chapter 7 CFD investigation of cross-sectional flow pattern of solid phase in a horizontal pipe 

Table 7.1 Numerical parameters for DPM simulations 

Type Choices 

Solver •v* Segregated solver with 2"' 

<- Space: 3D 

Unsteady simulation 

<- Time step: lxl0"3s 

order discrete scheme 

Turbulence model(k-e Model) 

Discrete phase option 

Gravity 

Wall collision model 

Model Constants: C m u =0.0845 

C, = 1.42C2=1.68 

RNG options: Differential viscosity model 

Near-wall treatment: standard wall functions 

Interaction with continuous phase 

Update DPM sources every 25 fluid phase iterations 

Saffman lift force 

Two-way turbulence coupling 

Developing user-defined-functions (UDF) to control 

particle number at each position at each injection moment 

A total of 1047 injection points which produce 53267 

parcels within a second. 

the negative direction of y axis 

Value: 9.81 m/s2 

Elastic collision model 

Restitution coefficients of normal and tangential directions 

are 1 

Smooth pipe 

Table 7.2 Numerical parameters for DEM-Fiuent calculations 

Type Values 

Fluent Solver Segregated solver with 2 n d

 order discrete scheme 

Space: 3D 

Unsteady simulation 

Time step: lxl0"3s 

Turbulence model(k-8 

Model) 

Model Constants: C m u =0.0845, C, = 1.42, C2=1.68 

RNG options: Differential viscosity model 

Near-wall treatment: standard wall functions 

Full buoyancy effects 

Gravity the negative direction ofthe y axis, Value: 9.81 m/s2 

EDEM Particles material 

Particle mean size 

Number of particles 

Poisson's ratio 

Restitution coefficient 

Particle factory (particle 

injection position) 

Spherical glass beads 

90um 

53267 within a second 

0.4 

1 

212 

Time step 

Shear modulus (Pa) 

lxl0"6s 

2.6x10s 

139 

VES017174 
A n investigation of particle dynamics in a dilute phase pneumatic conveying system 

7.2.2 Experimental rig and numerical geometry 

Figure 7.1 shows the experimental rig and the three meshed sections which schematically display 

the numerical domain. The domain is the l m long horizontal glass pipe (((>75mm) 90mm 

upstream of the elbow in order to compare the numerical results with the experimental data 

without the elbow effect on the upstream fluid. It has been meshed into 76400 triangular cells 

with a boundary layer of 5 cells thickness. Grid independence has been confirmed by single air 

phase flow calculations. 

Figure 7.1 Experimental rig and schematic diagram of numerical geometry 

7.2.3 Fluid conditions at inlet 

The initial conditions at the inlet for numerical simulations are generated following the 

experimental results. Using the extended LD A technique introduced in Chapter 3, we measured 

the cross-sectional distributions of air velocity, particle velocity and particle number rate on a 

series of pipe cross-sections within the numerical domain whose inlet locates 2.9m away from the 

particle feed position in the horizontal part of the experimental rig (as shown in Figure 7.1). In 

the experiments, glass beads with mean size 90pm (Stokes number 10.2) and density 2550 kg/m3 

were pneumatically transported by air with a conveying velocity of 12m/s. The experimental 

140 
Chapter 7 CF D investigation ol'cross-scctional flow pattern of solid phase in a horizontal pipe 

results at the inlet of the numerical domain are shown in Figures 7.2 and 7.3 for the air and solid 

phases respectively. 

'0.5 

40 20 

bp ""-I 

20 0 20 

z(mm) 

0.01 

5 O.0P 

0.019 

-40 -20 0 20 

Figure 7.2. Air velocity (U „ U, and Uz ) at inlet 

Figure 7.2 shows the distribution of the three components of air velocity at the section x=0mm 

(inlet), which were measured by LD A using smoke as seeding particles. The measured turbulence 

intensity ofthe air flow is about 3.5%. These experimental data was used as the velocity profile 

of the air phase at the inlet in the numerical simulations. 

U.. . U„ 

40 

20 

0 

-20 

•40 

-40 -20 

40 

20 

0 

-20 

px py 

13 

12 

0 20 40 

z(mm) 

-40 

>-os 

0.01 

-40 -20 0 20 40 

z(mm) 

40 

20 

0 

-20 

-40 

-40 -20 

v<*> 

.0> -o 

is 

K3 -O.^ 

0 20 40 

z(mm) 

Counts within 1s 

300 

40 

20 

0 

-20 

-40 

-40 -20 

too 

'200 900 

0 20 40 

z(mm) 

Figure 7.3. Cross sectional distributions of particle velocity 

and particle number rate at inlet averaged over Is 

With regard to the inlet conditions of the solid phase, the distributions of particle velocity and 

141 

VES017176 
A ii investigation o f particle dynamics in a dilute phase pneumatic conveying system 

particle number rate are illustrated in Figure 7.3, as measured under conditions of 1.6% solid 

loading ratio at 12m/s air conveying velocity in a <j>75mm pipe. It is clear that solid phase at the 

inlet is heterogeneous over the section, since particle velocity reduces from the centre to the wall 

and particle number rate increases from the top to the bottom. Thus the numerical simulations 

should be performed in the unsteady state. 

7.2.4 Experimental cross-sectional flow patterns of solid phase 

Particle number in 1s 

40 

20 

-20 

-40 

U p x (m/s) 

" 11.S 

&

1 1 ^ 

40-

20 

0 

-20 

-10 

100 

300 

500 

^ 500 § 

-40 -20 0 20 40 -40 -20 0 20 40 

z(mm) z(mm) 

Figure 7.4 The contours of particle velocity U p x and particle count over Is 

at the section x=455mm 

401 

20 

U

p x < m/s> 

c i. w 

£ 0 m 

>, o>*>. 

-201 1 

-40 

to W*5 

# 5 

-20 

-10

 ! 

Particle number in 1s 

40 

20 a 

ifi. 

% 500 

'500

 90 0 

-40 -20 0 20 40 

z(mm) 

-40 -20 0 20 40 

z(mm) 

Figure 7.5 The contours of particle velocity U p v and particle count over Is 

at the section x=l 000mm. 

In Chapter 5, the experimental cross-sectional flow patterns o f solid phase on a series of 

cross-sections have been displayed under the different fluid conditions. Here two selected 

142 

VES017177 
Chapter 7 CTTJ investigation o f cross-sectional flow pattern of solid phase in a horizontal pipe 

samples within the numerical domain are shown in Figure 7.4 and 7.5 which correspond to the 

mid section and outlet ofthe numerical domain. They will be used to compare with the numerical 

results. 

As shown in Figures 7.3, 7.4 and 7.5, we notice that the contours ofparticle horizontal velocity 

component (U p x ) at the three sections display a characteristically annular structure, and their 

annular cores or the fastest U p s regions are observed to be displaced upwards above the pipe 

centre line. The contours of particle number rate on the three sections reveal a characteristically 

stratified form. Consequently, the flow patterns of gas-solid flow over the pipe cross-sections can 

be described as an annular pattern in terms of horizontal particle velocity component and a 

stratified layer pattern in terms of particle number rate. 

7.3 RESULTS AND COMPARISONS 

7.3.1 Flow patterns of solid phase investigated by DPM 

Using DP M in Fluent, we simulated a total of 53267 parcels (the unit of particles in a trajectory 

at every time interval) passing through the domain from 1047 feeding points over Is. These feed 

points were the same as the sampling points in the experiments. Since solid mass flow rates at the 

feed points were different depending on particle number rate, an injection program utilising a 

user-defined-function (UDF) by using macros in Fluent was developed and coupled into Fluent. 

This determined the particle number injected from each point at every numerical time step. For 

unsteady-state simulations, the time-averaged values of parameters cannot be displayed by Fluent 

directly. The results were therefore post-processed and statistically analyzed using Matlab7.0. A 

selection of typical results is shown in Figures 7.6 and 7.7. 

143 

VES017178 
A il investigation ol particle dynamics in a dilute phase pneumatic conveying system 

{LWUa} at the momentt=200(ms) 

40 

20 

-20 

A.1 

7.7 

{Up x /Ua} atthe momentt=500(ms) 

40 -

20- 7 

*~ A A 

0 i ^ 

-> 

-20 ^ N N 

-40 

-40 -20 0 20 40 

z(mm) 

{IWUJatth e momentt=800(ms) 

40 1 

-40 

-40 -20 0 20 40 

z(mm) 

{<Up x /Ua>}over 1000 (ms) 

40 

20 -

I

 0 

A.1 

20 

1.1 

-20 

1.1 

1 

-40 -

-40 -20 0 20 

z(mm) 

-20 

7

-tt A.1 

A-1 

7 1 

j -40 

40 -40 -20 0 20 

z(mm) 

40 

Figure 7.6 Contours of the dimensionless particle instantaneous velocities )TJp,/U,) and its 

time-averaged value {<Upv/Ua>} over 1000ms on the section x=455mm obtained from 

simulation using FLUENT DP M (Ua=12m/s) 

Figure 7.6 shows three selected contours of the axial instantaneous particle velocity {Up x } and 

one time-averaged contour {<Up x>} over one second on the section x=455mnt. Observing the 

first three contours of particle instantaneous velocity U p x , we find that the contour shapes differ 

from each other. This means that the structure of the U p x contour is time-dependent. In addition, 

we also notice that some fragmented isolines displayed in all four diagrams of Figure 7.6. The 

time-dependent structure and fragmented isolines indicate that the gas-solid pipe flow is unsteady 

in time and heterogeneous in space. Compared with the three instantaneous contours, the contour 

ofparticle time-averaged velocity over Is (at the right bottom of Figure 7.6) more clearly shows 

the annular structure of gas-solid flow over the pipe cross-section. This annular structure is 

generally similar to the flow pattern portrayed by the experimental data of particle velocity U p x in 

144 

VES017179 
Chapter 7 CI-'D investigation o f cross-sectional flow pattern o f solid phase in a horizontal pipe 

Figure 7.5 and Figure 7.6. Their difference results from the fact that the fastest region or annular 

core in Figure 7.6 is displaced downwards below the pipe centre line, while the experimentally 

located annular core in Figure 7.5 is shifted upwards above the pipe centre line. However, the 

numerical annular pattern in Figure 7.6 is not uniform like the experimental one in Figure 7.5. 

{<Uot>} (m/s) on the section x= 455mm particle number N in 1s 

40 . 40. 

20 20; 

E n E 

£ a* ** " E 

-20

 v K ' -20 

13 

• ^ 

-40 . _ , -40 

too "to 

300 

-40 -20 0 20 40 -40 -20 0 20 40 

z(mm) z(mm) 

{<U >} (m/s) on the section x=1000mm particle number N in 1s 

40 - 40, 

20 20 

1A 13 | 

o -

 5 | o! 

-20 . ,3 p -20 i 

,00 

100 

ri 

^ - I 

-40 — • • - -40 I - - — -

-tO -20 0 20 40 -40 -20 0 20 40 

z(mm) z(mm) 

Figure 7.7 Contours of the time-averaged axial particle velocity {<Upv>} and particle number [N} 

over Is on two sample sections (x=455mm, 1000mm) obtained from FLUENT DPIVI 

Since the contours of time-averaged particle velocity U p x are useful to explore some 

characteristics of gas-solid flow, Figure 7.7 shows contours of time-averaged U p x and particle 

number rate at two sections at x-=455mm and 1000mm respectively. Comparing these flow 

patterns with those at the inlet indicated in Figure 7.3, both the annular structure in terms of U p x 

and the stratified shape layered by particle number rate are still shown in the contours at the 

x=455mm section, but these two characteristics are distorted to extinction in the contours at the 

x= 1000mm section. This shows that the DP M modelled flow pattern varies along the fluid 

direction. 

145 
A n investigation ofparticle dynamics in a dilute phase pneumatic conveying system 

7.3.2 Flow patterns of solid phase investigated by Discrete Element Method 

In the coupled Fluent & EDE M simulations, all numerical geometry, fluid conditions and 

boundary conditions were the same as the foregoing ones in the DP M simulations. But for 

particle injection at the inlet, particles could be automatically injected with a different mass flow 

rate at every injection point through defining "particle factories" over the inlet rather than using a 

U D F program to control the process of particle injection. Since the solid phase in the DE M is 

treated as individual particles dispersed in the fluid rather than as the "parcels" (groups of 

particles with the same trajectory) used in DPM , the effect of particle-particle interactions and 

friction due to collisions can be accounted for in detail in the DE M model implemented here by 

the EDE M software. Due to the need to transfer particle locations back to the fluid domain at 

each fluid time step, and the large size of domain relative to the particle size and number, the 

speed of this coupled simulation is rather slow. Typical results of the time-averaged contours of 

particle velocity U p x and particle number rate are shown in Figures 7.8. 

{<U >} (m/s) on the section x= 455mm 

40 40, 

particle number {N} in 1s 

20 

-20 

20 

?00 

300 too % 100 

w

3o° 

o • . 

o 10Q ' § 

% 1

 500 % 200 

1000 

2000 ,tj 

-40 .. . 

-40 -20 0 20 

z(mm) 

40 

(<U >} (m/s) on the section x=1000mm 

px 

40 , 

-40 > 

-40 -20 

40 

0 20 40 

z(mm) 

particle number {N} in 1s 

20 20 

-20-

12 

-40 

-40 -20 

"12 

11 « 

0 20 40 

z(mm) 

0, 

-20 i 

-40 

-40 -20 0 20 40 

z(mm) 

Figure 7.8. The flow patterns of particle mean velocity and particle number on two sample 

sections (x=45Smm, 1000mm) obtained by using FLUENT & EDEM 

146 

VES017181 
Chapter 7 CF D investigation of cross-sectional flow pattern of solid phase in a horizontal pipe 

On the section x=455mm, an annular flow pattern of solid phase in terms of the particle velocity 

horizontal component (U, n ) (to be compared with Figures 7.4 and 7.7) is obvious in the upper 

section of Figure 7.8, and the core region is also displaced downwards below the pipe centre as in 

the DP M results. However, the stratified flow pattern observed in Figures 7.4 and 7.7 is 

completely distorted in the upper section of Figure 8. A s for flow patterns on the x=1000mm 

section, both the annular pattern and the stratified pattern are skewed, and no clear pattern can be 

observed in Figure 7.8. 

7.4 DISCUSSION 

0.5 ; 

0 x= 300mm 

-0.5 -

0 9 0.95 1 1.05 1.1 1,15 1.2 1.25 

1

 ii 

0.5 -

Q; 0 x= 700mrn i 

-0.5 

-1 

0.8 0.9 1 1.1 1.2 1.3 

{<U »/U ) 

p. a' 

Figure 7.9 Comparison of the numerical and experimental vertical profiles of {<Upx>/Ua} at 

four different positions along the fluid flow direction (the continuous blue line is the profile at 

inlet) 

In order conveniently to access the evolution of flow patterns along the pipe, the experimental 

and numerical profiles of the dimensionless {<Up. x>/Ua ) and particle number over Is at the 

z=0mm lines at several sections (x=300, 455, 7000 and 1000mm) are plotted in Figure 7.9 and 

Figure 7.10. U p x is normalized by the mean air conveying velocity (Ua ) which is 12m/s. 

In general, profiles at the position o f x=300mm have a good agreement with each other as well as 

similarity to the profile at inlet, although the peaks of both numerical profiles of {<Up x>/Ua} 

show a small shift away the pipe centre line. At the further downstream distance of x=455 to 

0.8 0.9 

Intel 

L D A 

D P M 

D E M 

g 0 . x=1UUUrnm 

{<u >/u) 

1.2 1.3 

(<U >/U ) 

1.2 1.3 

147 
A n investigation of particle dynamics in a dilute phase pneumatic conveying system 

I OOOmm, there is much discrepancy among these profiles. Especially at the position of 

x1000mm, both numerical profiles of {<Up x>/Ua } have been distorted, which are completely 

different from the experimental profile of {<Up x>/Ua } as well as the profile at inlet. By contrast, 

the experimental profiles of {<Up x>/Ua} can be observed to be similar at the different positions 

along the pipe. 

Particle number N over 1s Inlol 

LDA ; 

DPM j 1 r 

OEM | ! 

0.5 i 

500 1000 1500 2000 2500 

Particle number N o\er 1s 

500 1000 1500 2000 

Panicle number N over 1s 

500 1000 1500 2000 

Particle number N o\er 1s 

Figure 7.10 Comparison ofthe numerical and experimental vertical profiles of particle number 

over Is at four different positions along the fluid flow direction 

As for particle number counted over Is, Figure 7.10 shows its numerical and experimental 

profiles at the four different positions along the pipe. On the whole, we can see that the 

experimental profiles of particle number are identical to each other and they also just vary around 

the profile of particle number at inlet with a small deviation. With regard to the numerical 

profiles of particle number over Is, there is a significant discrepancy among them along the fluid 

flow direction. Both numerical profiles show that there is an increasing tendency of particle 

number along the pipe, for particle number gradually increases at pipe bottom and decreases at 

pipe upper half, even where there is a very dilute or empty space without particles in the pipe 

upper space at the position x= 1000mm. 

However, experimental data in Figures 7.3, 7.4 and 7.5 shows that both the annular flow pattern 

and stratified particle number distribution follow a steady trend along the downstream direction 

in the whole domain. This indicates that using DP M or DE M can only estimate flow patterns 

148 
Chapter 7 CFD investigation of cross-sectional flow pattern of solid phase in a horizontal pipe 

properly within a short domain. In another words, both DPM and DE M have not yielded 

satisfactory results for predicting some parameters related to particle spatial distribution in the 

gas-solid pipe flow. 

In the previous two sections, the cross-sectional flow patterns and their evolution in the 

downstream direction, as calculated using two numerical methods, were discussed. Comparisons 

of the numerical results with the corresponding experimental data indicate that numerically 

predicted cross-sectional flow patterns show reasonable agreement with experimental ones only 

at pipe cross-sections located within a specific distance from the inlet. At greater downstream 

distances, numerical flow patterns become distorted until they are completely different from 

experimental flow patterns. This discrepancy means that the spatial distribution of 38-1 lOum 

particles being transported in the dilute state in a long horizontal pipe is not properly estimated 

by the current numerical methods. 

The numerical results of Huber (1998) showed 40um glass beads' 2D trajectories on a vertical 

section of a <|>80mm horizontal pipe. As would be expected since their Stokes Number was 2.0, 

the trajectories of these glass beads followed the fluid flow pattern. Furthermore, Sommerfeld 

(2003) numerically investigated trajectories of four different size glass beads in a 2D horizontal 

channel with 35mm height and 6m length. Without considering the effect of wall roughness, his 

numerical results show that all trajectories of 1 lOum particles end up on the channel bottom by 

3m downstream of the inlet. This is similar to our numerical results ofparticle number in Figures 

7 and 9. To allow for the problem of irreversible deposition, Sommerfeld introduced a model of 

particle-wall collision which assumed particle impact angle composed of the particle trajectory 

angle and a random normal distributed component due to roughness. The trajectories of HOum 

particles were then much widely distributed over the whole channel space and agreed with his 

experimental data. 

In summary, the foregoing discussion reveals that there still exist some effects which have not 

been accounted for in the current DPM or Fluent & EDEM coupling simulations for investigating 

gas-solid pipe flow. The model of particle-wall collision introduced by Sommerfeld will be 

incorporated in future coupling simulations and methods of two-dimensional pattern recognition 

will replace the current one-dimensional technique to precisely determine the similarity of fluid 

patterns of the solid phase on a series of pipe cross-sections. 

7.5 CONCLUSIONS 

Based on experimental data and the geometry of the experimental rig, flow patterns on a series of 

149 
An investigation of particle dynamics in a dilute phase pneumatic conveying system 

pipe cross-sections and their vertical profiles along the pipe have been numerically investigated 

by the standard DPMs of Fluent and Fluent coupled with EDEM . Three conclusions can be 

deduced from the comparison of numerical and experimental data. 

The annular structure of the particle velocity horizontal component and the stratified structure by 

particle number can be predicted by both Fluent DPM and Fluent & EDE M within a certain 

distance from the inlet, which can be estimated by the product ofparticle mean velocity and half 

the particle free falling time. On pipe cross sections further downstream, the flow patterns 

modelled are distorted until the annular velocity and stratified particle number characteristics 

completely disappear. Compared with the contour of particle number and its evolution along the 

pipe simulated using Fluent DPM, the data achieved by using Fluent & EDEM shows that 

particles distribute much widely in the pipe space, rather than being located close to the pipe 

bottom after they have been transported a critical downstream distance. This means that 

considering the effect of particle-particle interactions in DE M will improve the accuracy of 

numerical simulations for gas-solid horizontal pipe flow, even though (he solid phase is in a 

dilute state. The distorted flow patterns and their evolution profiles along the pipe indicate that 

particle spatial characteristics found from experiment are not properly estimated by the current 

numerical models. Thus, the micro-mechanism of fine particle transport in pipes should be 

further studied. 

Finally, it should be mentioned that work on developing the current numerical model using our 

experimental data is ongoing. 

150 

VES017185 
Chapter 8 

Conclusions 

Co-firing applications in power stations have been confirmed as being a promising way to reduce 

C 0 2 emissions very considerably while generating enough electricity for energy demand. A 

demanding task is that of controllably distributing a fuel mixture of pulverized coal blended with 

biomass particles in a common pipeline, which is likely to save much investment as success 

would enable existing pulverized fuel boilers to be used for biomass exploitation. Therefore, to 

address the problem of controllable distribution in co-firing techniques and to gain an improved 

understanding the mechanism of pneumatic conveying, this research into particle dynamics of 

pipe flow was undertaken. 

The objectives of this research were, firstly, to numerically evaluate the influence of various 

factors on the behaviour of particles of the different materials in a horizontal pipe flow; secondly, 

to develop an extended technique of Laser Doppler Anemometry in order to determine 

cross-sectional characteristics of the solid phase in the horizontal and vertical sections of a 

pneumatic conveying system; thirdly, to develop a novel imaging system for visualizing particle 

properties by using a high definition camcorder on a cross-section illuminated by a halogen light 

sheet; and, finally, to make a comparison of the cross-sectional characteristics revealed by 

experiment and those simulated by using the Discrete Phase Model of Fluent and the coupling 

calculations of Fluent & EDE M respectively. 

Conclusions of the experimental and numerical investigations are detailed below. 

8.1 SUMMARY OF RESULTS 

The overall results from this study cover particle dynamics in horizontal pipe flow and in a 

vertical pipe flow downstream of right-angled elbow. The main results are summarised as 

follows: 
An investigation of particle dynamics in a dilute phase pneumatic conveying system 

1. Critical parameters and particle similarity in a horizontal dilute phase pneumatic 

conveying system 

Using the Discrete Phase Model in Fluent 6.2.16, we have explored the influence of air 

conveying velocity, pipe roughness and particle size on particle trajectories in the boundary 

region. The numerical results demonstrate that the Saffman Force plays an important role in a 

dilute pneumatic conveying system, especially for determining whether a particle will be 

re-suspended from the boundary region. This analysis shows that there exist three critical 

parameters: 

(1) The critical air conveying velocity. A higher air conveying velocity generally benefits by 

lifting a particle higher from the boundary region towards the mainstream field of pipe flow, 

but the height reached is no longer much enhanced when the air velocity is more than 30m/s 

in our numerical model. This value is defmed as the critical air conveying velocity. 

(2) The critical pipe roughness. In the pipe boundary region, increases in pipe roughness 

result in a particle being able to jump to a much higher position. However, when the pipe 

relative roughness is more than 1.64%, the trajectories of the particle are the same and the 

particle is no longer lifted much higher. The value of 1.64% is termed the critical pipe 

relative roughness for the current fluid conditions of air conveying velocity 24m/s. 

(3) The critical particle size. Basically, the bigger a particle is, the higher it can be suspended 

if its size is in the range of 10~100um. However, this phenomenon no longer exists when a 

particle is larger than 100pm. The value of 100pm is defined as the critical particle size for 

the current fluid conditions of air conveying velocity 24m/s. 

(4) The characteristics of the dimensionless mean particulate velocity. The numerical 

results indicate that particle mean velocities of the different materials can be classified into 

three regions in the horizontal and vertical directions, non-dimensionalising by means of the 

Stokes Number or divided by the terminal velocity respectively. Particles with a Stokes 

Number less than 1 have a mean velocity equal to the air conveying velocity in the horizontal 

direction and a mean vertical velocity equal to the terminal velocity in the fully developed 

region. Correspondingly, for larger particles with Stokes Number more than 3.5, their mean 

dimensionless velocity U p x / U a (the horizontal particle velocity divided by air conveying 

velocity) tends towards 0.6 in the horizontal direction and their mean dimensionless velocity 

Upy/Ua (the vertical particle velocity divided by air conveying velocity) in the vertical 

direction becomes essentially zero. The mean dimensionless velocities of particles with 

Stokes number between 1 and 3.6 are in the range of 0.6-1 in the horizontal direction and 

-1-0 in the vertical direction (as the direction of gravity). 

2. The extended technique ofLaser Doppler Anemometry 

152 

VES017187 
Chapter 8-Conclusions 

So far, there is still a lack of papers discussing the detailed effect of refraction at the pipe 

wall and of sample rate in gas-solid flow measurements using Laser Doppler Anemometry. 

The refraction effect due to the curved surface of the pipe can not be ignored and the 

sampling rate is related to the statistically accuracy of calculating the time-averaged value of 

a parameter measured by LDA , we have proposed modifications to the current normal 

technique of LDA , which has been validated by fhe comparison of the profiles of air velocity 

measured by LD A and the corresponding theoretical profile estimated by the empirical 

one-seventh power law of air velocity in a pipe. This extended technique has been applied to 

measure the cross-sectional velocity distribution of the air phase in a vertical pipe 

downstream of a 90° elbow. The contributions of the newly-developed techniques consist of: 

(1) Buildine a mathematical model for calculating the transform matrix of the three pairs 

of LDA laser beams. The transform matrix is used to map the actual position of the 

measurement volume of LD A in pipe flow according to probe angle, for any change affected 

by shifting the three-dimensional traverse system. 

(2) Determining a suitable sample rate for LDA experiments. A suitable sample rate (10K 

Hz) for LD A has been experimentally determined for 70-1 lOum glass beads conveyed by a 

12m/s air velocity with a solid loading ratio of 1.6% in (j>75mm pipe. This sampling rate 

applied to the experiments ensures to accurately calculate the local time-averaged particle 

velocity at any sample point. 

(3) Confirming the profile of air velocity in a horizontal pipe. The experimental data show 

that the profile of air velocity measured by LD A in a horizontal pipe is in good agreement 

with the empirical one-seventh power law. Similarity among cross-sectional distributions of 

the axial air velocity on different horizontal cross-sections indicates the stability of fully 

developed gas pipe flow velocity profile. The axial air velocity shows an annular distribution 

over a cross-section. 

(41 Cross-sectional characteristics of the air velocity in a vertical pipe downstream of a 90° 

bend. On vertical cross-sections, the air velocity distribution at no longer maintains the 

annular velocity contours in horizontal pipes. The cross-sectional distribution of the axial air 

velocity shows contours resembling a horseshoe in shape at the elbow outlet, where air flow 

being faster in the region close to the pipe bend's outer wall (outside the horseshoe ) than in 

the region inside the horseshoe, in the pipe centre and close to the inner wall of the bend. 

Further downstream, the differences of axial particle velocity between the horseshoe inside 

and its outside gradually decrease. A comparison of the experimental data and the numerical 

results generated by using CFD indicate that both of them show similar results of air velocity 

evolution in the horizontal pipe after the elbow. 

153 

VES017188 
An investigation of particle dynamics in a dilute phase pneumatic conveying system 

3. Cross-sectional characteristics of the solid phase 

By applying the extended LD A technique, we have investigated particle dynamic behaviour 

of three types of glass beads which are selected to simulate to simulate the pulverised coal 

and biomass pellets transported in a dilute pneumatic conveying system. Detailed 

information on the cross-sectional spatial distributions of the axial particle velocity and 

particle number rate is reported. 

(1) Annular cross-sectional flow pattern of solid phase bv the axial particle velocity. In a 

horizontal pipe at the minimum air conveying velocity lOm/s, the experimental data on a 

series of cross-sections clearly illustrate that the axial particle velocity distribution over a 

horizontal cross-section is annular, resembling that of the air phase, for particles with Stokes 

number less than 16. For particles with a Stokes numbers greater than 16, the characteristics 

of this annular structure become weak. 

(2) Stratified cross-sectional fluid pattern of solid phase bv particle number rate. In a 

horizontal pipe at the minimum air conveying velocity lOm/s, the experimental contour of 

particle number rate (counting in one second) over a horizontal cross-section displays a 

stratified configuration, especially for glass beads with Stokes number less than 16. 

(3) Evolution of the two cross-sectional fluid patterns. These two types of cross-sectional 

flow patterns (for the axial particle velocity and particle number rate) can be observed at a 

number of positions along the pipe axis, but the position of the annular core and the values of 

iso-lines are dependent on particle size and vary along the fluid direction. 

(4) Cross-sectional characteristics of particle velocity in a vertical pipe downstream of a 

90" bend. In the vertical pipe after an elbow (R/D=1.3, R being the bend radius and D the 

pipe diameter), a horseshoe-shaped feature has been observed in the cross-sectional 

distributions of the dimensionless axial particle velocity for all three types of glass beads 

(less than 50pm; 70-110 pm and 180-300 um) on the section 0D close to the elbow outlet. 

Further downstream, the horseshoe feature is gradually distorted until it completely 

disappears and the axial particle velocity is fairly uniform. This degradation distance is about 

4D for the first type of glass beads, 2D for the second type and ID for the third. 

(5) Cross-sectional characteristics of particle number rate in a vertical pipe downstream of 

a 90" bend. The cross-sectional distribution of the dimensionless particle number rate on the 

section 0D shows that the rope is formed at the pipe outer wall where the maximum particle 

number rate occurs. On the whole, the rope formed by the first type of glass beads (less than 

50 um diameter) can still be observed at the section 6D. For the second type of glass beads 

(70~110um), its rope is re-distributed across the pipe cross-section from the section 4D 

according to the similarities between cross-sectional distributions of the dimensionless axial 

particle velocity and the dimensionless particle number rate. Overall, roping is not obviously 

154 

VES017189 
Chapter 8-Conchisions 

shown in the gas-solid flow of the third type of glass beads (180-300 um) downstream of the 

section OD. This suggests that larger particles are less prone to form ropes and dissipate more 

easily when they do, perhaps due to the greater inertial influence on their behaviour. 

4. Visualization of particle dynamics on a cross-section 

In order to visualize particle dynamics on a cross-section, a video & image processing 

system for measuring particle size and analyzing particle spatial characteristics over a 

horizontal pipe cross-section in a dilute pneumatic conveying system was developed. A light 

sheet produced from a halogen lamp box was used to illuminate and section the gas-solid 

flow over a pipe cross-section. A high definition camcorder (1900ixl008i pixels, 25 frames 

per second) was utilized to record particle behaviour over the highlighted region. 

(1) Decoding algorithms for uncompressed MPEG-2 videos. A set of video algorithms was 

developed to decode the compressed MPEG-2 videos into AVI format for further image 

processing. An AVI video, like a database, consists of a series of uncompressed frames. Each 

pixel on each uncompressed frame is directly mapped to a spatial point in the measurement 

region for further image processing. 

(2) Image processing algorithms for making each colour frame binary. First, each color 

frame extracted from an uncompressed AVI video is converted into the corresponding 

gray-scale picture according to the particles' luminance information. Secondly, this picture is 

denoised by a Wiener filter. The third step is that a background image is obtained through 

removing the particle images in the denoised picture using a 25 x 25 Median Filter. In this 

way, the features of the background environment can be preserved. Subsequently, when a 

separated background image is subtracted from the denoised image, the heterogeneous 

background is removed. The subtraction result of a gray image is then converted into a 

binary image using Otsu's method. 

(3) Extraction of particle characteristics from a binary image. The features of every particle 

such as shape, size and spatial position can then be extracted by applying the Chain Code 

Technique, which stores the relative co-ordinates between consecutive pixels, and records the 

shape of a region by analyzing each point on the boundary in sequence and assigns a code to 

denote fhe spatial direction between two adjacent points. Then the particle size distribution 

and the mean size over a section can be calculated from the set of Chain Code. 

(4) Cross-sectional characteristics of particle size distribution. Experimental results of 

particle size and size distribution on each frame suggest that gas-solid pipe flow is always 

heterogeneous in space and unsteady in time. The particle mean size by mass fluctuates less 

with time and is thus more suitable for statistical descriptions of the unsteady properties of 

gas-solid pipe. Both the contours of particle number rate and particle time-averaged 

155 

VES017190 
An investigation of particle dynamics in a dilute phase pneumatic conveying system 

concentration exhibit the stratified structure characteristic of particle flow in a horizontal 

pipe cross-section. This kind of stratified structure is similar to the results revealed by Laser 

Doppler Anemometry 

5. Discrepancies between experimental data and numerical results in respect of particle 

cross-sectional distribution 

Based on experimental data and the geometry of the experimental rig, flow patterns on a 

series of pipe cross-sections and their vertical profiles along the horizontal pipe have been 

numerically investigated by the standard Discrete Phase Mode of Fluent and Fluent coupled 

with EDEM to account for the effects of particle-particle collision. Three conclusions can be 

deduced from the comparison of numerical and experimental data. 

(1) Region with a eood agreement between the numerical results and the experimental 

data. The annular structure of the particle velocity horizontal component and the stratified 

structure by particle number can be predicted by both Fluent DPM and Fluent & EDEM 

within a certain distance of the inlet, which can be estimated by the product ofparticle mean 

velocity and half the particle free falling time. On pipe cross sections further downstream, 

the flow patterns modelled are distorted until the annular velocity and stratified particle 

number characteristics completely disappear. 

(2) Advantages of considering particle-particle interaction in numerical simulations. The 

comparisons of numerical and experimental cross-sectional flow patterns of solid phase show 

that there is reasonable agreement at pipe cross-sections located at horizontal positions less 

than half the product of particle mean velocity and mean free fall time in the pipe from the 

particle inlet. Further away from the inlet, the numerical results show flow patterns which are 

increasingly divergent from the experimental results along the pipe in the direction of flow. 

This discrepancy indicates that particles' spatial distribution in a pipe is not accurately 

predicted by DPM or Fluent coupled with DEM. Thus, the micro-mechanism of fine particle 

transport in pipes should be further studied. 

8.2 RECOMMENDATIONS FOR FUTURE WORK 

The findings that arise from this project relating to the experimental and numerical analysis of 

particle behaviour have explored some fundamental characteristics of particle dynamics in a 

dilute pneumatic conveying system. Due to the complexity of the phenomena involved, research 

into gas-solid pipe flow is still an ongoing area of interest, especially for a multiple-component 

solid phases. Three possible extensions of the current work should be carried out in further 

156 

VES017191 
Chapter 8-Conclusions 

studies. 

First, in order to obtain empirical equations for particle dynamics in pipe flow, especially in a 

vertical pipe downstream of a 90° bend, more experimental work using the extended technique of 

Laser Doppler Anemometry should be carried out to determine the behaviour of different 

granular materials under a wide range of fluid conditions. Our current work only focused on low 

air conveying velocities. 

Second, the video & image processing system developed in this work should be used to measure 

the size and spatial distribution of particles more than 80(im in diameter over a whole 

cross-section of <|>75mm pipe. This visualization system can be made suitable for fine particle 

measurements using a smaller diameter of pipeline for experiment. In addition, using coloured 

granular materials, this system can be developed into a measurement tool for gas-solid pipe flow 

with a multi-component solid phase through adding a function capable of discerning particle 

colour. 

Third, existing models of particle-particle interaction and particle-wall collision should be 

investigated in detail and modified to explain and eliminate the discrepancies between the current 

numerical results and fhe experimental data. 

Fourth, statistical analysis and further experimentation should be undertaken to quantify the 

reliability ofthe LD A results and to estimate the error in the final values. 

8.3 PUBLICATIONS ARISING FROM THE PROJECT 

Lu Y., Glass H. D., Easson J. W., (2009). An investigation of particle behaviour in gas-solid 

horizontal pipe flow by an extended LD A Technique. Fuel. Accepted (JFUE-D-08-00741). 

Lu Y , Glass D. H., Easson W. J., (2008a). Investigating particles behavior in gas-solid horizontal 

pipe flow by an extended Laser Doppler Anemometry Technique. In: Proceedings of 7th 

European Conference on Coal Research and its Applications, September 2 n d - 5th, Cardiff, 

UK. 

Lu Y , Glass D. H. , Easson W. J., Crapper M. , (2008b). Investigation of the Flow Patterns of 

Gas-solid granular flow in a horizontal pipe by FLUENT & EDEM . In: Proceedings of 

Particle Systems Analysis 2008, September 1st - 3rd, Stratford, UK. 

Lu Y , Glass D. H., Easson W. J., (2007). Investigating Flow Properties of Coal Biomass Blends 

in Pneumatic Conveying Systems by Computational Fluid Dynamics. In: Proceedings of 

2007 international conference on Coal Science and Technology, August 28lh- 31lh, 

Nottingham, UK. 

157 
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