Kyushu University Global COE Program
Journal of Novel Carbon Resource Sciences, Vol. 3, pp. 17-20, Feb. 2011

Numerical Analysis of Particle Separation and Flow Characteristicin Non-woven Filter
Shinya Abe*1, Gen Inoue*2, Yosuke Matsukuma*2, Masaki Minemoto*2*1

Graduate School of Engineering, Kyushu University*2
Faculty of Engineering, Kyushu University(Received November 12, 2010; accepted January 18, 2011)
In order to improve the performance of the non-woven filter used for IGCC process, it is very important to know
the particle behavior in the non-woven filter. In this study, numerical simulation method considered the non-uniform
structure is newly proposed in order to predict micro-particle behavior in complex structure. As a result, the particle
behavior in the non-woven filter was able qualitatively to be figured out and it is found that the particle adhesion
behavior and the internal distribution depend on the transfer parameter of structure. Furthermore, we made the filter
characteristic map concerned the behavior of particle adhesion.

In recent years, depletion of energy source andenvironmental problem has grown into serious problems.
Coal has comparatively large amount of deposit, and canbe stable source of energy. However, coal emits morecarbon dioxide per unit heating value during burning
than oil or natural gas. Thus, from the viewpoint ofpreventing global warming, Integrated coal Gasification
Combined Cycle (IGCC) which is one of the highefficiency and environmentally-friendly energy systems
is expected. In the IGCC process, micro-particles
contained high temperature gas was collected to prevent
degradation of gas turbine. Though there are various
methods of the collection of microscopic particles, fromthe viewpoint of pressure drop treatment and mechanicalstrength, the collection with the non-woven filter iseffective for a large-scale exhaust gas treatment suchas thermal power plant and waste incineration plant. In
the collection with the non-woven filter, the filter andother materials can be broken due to increase pressure
drop by particle adhesion, so it is essential to brushdown the micro-particle, called by “back washing”.
Therefore, the non-woven filter used in the collection
process is required not only collection efficiency but also
aeration performance to decrease running cost in thewhole system. In addition, considering high efficiencyof various combustion engines, high temperaturecollection is very important. However, the relationshipbetween these characteristics and structure has neverbeen fully understood yet because it has microscopic andcomplex structure. Therefore, it is difficult to evaluate
the relationship directly by only experiment. In thisstudy, to improve filter performance, the flow collection
considered the non-woven structure was calculated, andthe characteristic of various structures were examined.

2. Numerical analysis
2.1 Non-woven filter

The characteristic of the non-woven filter used fornumerical analysis was obtained by actual non-woven
filter. Fig.1 shows image of the actual non-woven filterby microscope. From this image, the fiber diameter (df)

was obtained. In addition, the porosity (ε) was obtainedby calculating from filter volume, mass and density. With
these data, simulated non-woven filter was made, shownin Fig.2. The simulated non-woven structure was madeby arranging the straight fiber randomly and by stacking
the fiber in layers1). In this method, it was assumed to bepenetration of the fiber and not to be distortion of thefiber.

z[μm]1. Introduction

10050
400

100μm

300
200
y[μm]

Fig. 1

Actual filter.

2.2 Multi-blocking

Fig. 2

100

100

200

300

400x[μm]

Simulated filter.

In order to calculate the particle concentration
distribution with flow, multi-block simulation wasdeveloped. First, to use the property data of simulated
structure in the flow collection calculation, the simulated
non-woven structures were changed the multi-blocking
each 10 mesh, and local transfer parameter such asporosity, pore size and permeability were given. Fig.3
is the conceptual diagram of the multi-blocking for
simulated non-woven filter. The property data between
each block was obtained by the following methods; 1)
porosity was given by void ratio of the filter structure, 2)pore size was given by filling virtual sphere in void space,3) tortuosity was given by using random-walk methodthat effective transfer length was calculated by moving
randomly in void space, 4) permeability was given byapproximating adjacent block by single channel. In thisway, gas and particle transport in heterogeneous porous
structure can be calculated at high speed.
To confirm the validity of simulated non-woven filter,pore size distribution and permeability obtained by theexperiment was compared. Fig.4 shows the pore size dis-

Journal of Novel Carbon Resource Sciences, Vol.3, Feb. 2011

Void space

Void space

30201010203040

10 205030 4050Fig. 3 The concept ofmulti-block structure.

Experiment4.612×10-13 m2

Calculation

4.358×10-13 m2

TS model4.210×10-13 m2

Filterwall

Table 1 The comparison ofpermeability (through-plane)

5040

assumed as a wall condition. As shown in Fig.5, the gas
including the particles inflowed from the bottom side.
Time step (t) is 1.0×10 -4s. Particle condition was set as
follows; diameter 0.1μm, volume 5.24×10 -22m3, density
2.26×106g/m3. In addition, the inlet particle concentrationand the flow rate were set 0.261g/m3 and 3.35×10 -9m3/s
respectively3). Though it was necessary to set the valueof Ad by the experiment originally, it was set constant
1.0×1016 m-2s-1 in this study.

wall

tribution of simulated and actual non-woven filter. The
pore size distribution of actual filter was obtained bybubble point method. In Fig.4, it was found that two kindof the peak pore size was almost equal. Table 1 shows
the permeability obtained by experiment, flow simulation and TS model. The permeability obtained by experiment was calculated by Darcy equation with air flow,
thickness pressure drop of through-plane. TS model isthe equation of anisotropic permeability in fibrous porous media2). In Table 1, all of these values were almostclose. From these results, the validity of this filter structure could be confirmed.

inflow

Fig. 5Computational system image.

3. Result1050840630420210001000.1

110
Pore size[μm]Fig. 4The effect of void structure on the adherent condition
was examined. Two kinds of structures with different
fiber arrangement were compared with each other. The
fiber diameter and the porosity were constant. One has
the non-uniform structure (a) and the other has uniform(b), and these figures are shown in Fig.6. In addition, thepore size distribution and the time variation of pressure
drop in the two structures are shown as Fig.7 and Fig.8.
In Fig.8, dimensionless time t0 was defined as follows;

Experiment[% ]Portion[%]Differential pore volume
dV/dlogR[cc/log(μm)]

Calculation[cc/log(μm)]

t0 =Pore size distribution.

2.3 Filter simulation

In order to calculate the particle transfer, the following
equation was used.

∂εC p∂t= −v ⋅ ∇(εC p ) − m p Ad S eff(1)where Cp is the particle concentration, ε is the porosityand v is fluid velocity. mp is the particle mass, Seff is the
local effective specific surface area in the non-woven
filter and Ad is the particle attachment coefficient wedefined. In this flow simulation, it was assumed thatcollected particles was dealt with continuum modeland calculated as particle concentration transport,
and that adhesion rate was a function of only surfacearea. Fig.5 shows computational system image. The
computational system is 100×100×78 blocks. The filter
size is 100×100×30 blocks. Ambient conditions weretd vz(2)

where d is the filter thickness and vz is average flow rateto direction of filter thickness. From Fig.8, it was foundthat the pressure drop increased with time because ofadhesion and that filter structure affected the variationof pressure drop. Fig. 9 shows the behavior of particle
adhesion in the different structures. In Fig.9, (a) is ununiform filter structure and (b) is uniform filter structure.
The filter was set in the area of surrounded by white line.
The back gradation shows pressure drop and gray object
is the adhesion particles. In this figure, the filter structure
was not drawn due to the visualization of adhesion
particles and the adhesion particles were drawn as theparticle concentration distribution that is not individual
particles. In Fig.9, it was confirmed the particle adhered
near bottom side of filter at first and that particles trappedat the inside part of filter with time. Particles adheredat the bottom surface of filter as a layer. On the otherhand, compared with non-uniform filter, it was foundthat more particles adhered at the inside of filter in thecase of uniform structure in Fig.9 (b). Though the timeof particle adhesion is short, it was thought to be due toassume that Ad is constant. From these results, it wasconfirmed that the variation of pressure drop and the partof adhesion depended on the filter structure.

300
200

200

300
200100(a)(b)

300

200

100

200

100

y[μm]

300

x[μm]

200

200

150

150

100

25

200

x[μm]

0(a)

Fig. 7 Pore size distribution by differential structure.
1098
76543210Pressure drop[kPa]no-nuniform structure
uniform structure

3025t0[-]18Fig. 8 The time variation of pressure drop bydifferential structure.
Next, the influence of structural properties on thedistribution of particle adhesion was examined. Fig.10
shows the internal distribution of particle adhesion in
the case of each porosity (a) and fiber diameter (b). In
this graph, x-axis is the filter thickness and y-axis is theamount of the particle adhesion, and the small valueof x-axis shows the bottom side of filter. In Fig.10, thesmaller the porosity and the fiber diameter are, the larger
the amount of the adhesion on the inflow side is. In otherwords, particles were caught on the surface of filter. On
the other hand, when the porosity and the fiber diameterare large, the particle attachment has happened to theinside. Table 2 shows the pressure drop in each structuralcondition. In this table, it was confirmed the pressure
drop increased as the porosity and the fiber diameterdecreased.

(b)
4000

6000

300

200

8000

ε=0.4
ε=0.6
ε=0.8

15
10501020
Filter thickness[μm]3035312100x[μm]2030-56

Amount of adhesion[10 g/m ]0100

df =3.0μm0(b)200y[μm]35

310-51
Pore size[μm]Amount of adhesion[10 g/m ]0.12000300

Time variation of particle adhesion in(a) non-uniform, (b) uniform structure.
(left: t0 =4.2, right: t0 =8.3)

10(a)

300

200Pressure [Pa]Fig. 90200

100

20

5100x[μm]100300100y[μm]

1510050300

no-nuniform structure
uniform structure

200y[μm]

(a)

5030

Differential pore volume
dV/dlogR[cc/log(μm)]

50

300

x[μm]

Fig. 6 Simulated filter (ε: 0.4, df: 3.0μm).
(a) : non-uniform structure and (b) : uniform structure

100

50

100y[μm]x[μm]

150

100

200

100

100y[μm]

300200150z[μm]300200z[μm]

z[μm]

9060
30z[μm]906030z[μm]Z[μm]Numerical Analysis of Particle Separation and Flow Characteristic in Non-woven Filter

25

ε=0.4

df =3.0μm
df =6.0μm
df =8.0μm

2015105001020
Filter thickness[μm]30Fig. 10

Internal distribution of particle adhesionin differences of (a) porosity and (b) fiber
diameter (t0 =8.3).

Table 2Pressure drop in the variable parameters(t0 =8.3)
ε[-]

P[Pa]

df[μm]

P[Pa]

0.40.60.85300
380753.04.0
5.05300
1720
790

Journal of Novel Carbon Resource Sciences, Vol.3, Feb. 2011

Time ratio ofrapid pressure drop (Tp) [s/s]As explained above, the smaller the porosity and thefiber diameter are, the larger the amount of the adhesionon the inflow side is. Furthermore, it is easy to remove
adhesion particles from the filter because the particles
were collected the surface. However, in this case, it isneeded to brush down adhesion particles immediately
because the pressure drop was increased rapidly.
From these results, we summarized in Fig.11 as filter
characteristic map concerning the behavior of particle
adhesion. In Fig.11, x-axis is the particle adhesion ratioon surface of filter (As) and y-axis is the ratio of the time
until completely obstructed filter by particle adhesion
to the time of standard filter (Tp). The data of standard
filter is porosity 0.64 and fiber diameter 3.0μm. Then, toimprove the filter performance, both value of As and Tp
have to be increased from the viewpoint of the smooth
removal of adhesion particles and the decrease of thecycle of back washing. Furthermore, it was found that
there is a difference in filter performance by two kinds ofstructures with different fiber arrangement. In this way,
it is necessary to consider the effect of not only overall
structural properties such as porosity, fiber diameterand pore size but also heterogeneous structure on filterperformance.

4. Conclusion

New simulation method was proposed in order topredict micro-particle behavior in the heterogeneous
filter structure. The behavior of particle adhesion andthe internal distribution could be calculated in eachsimulated structures. As a result, it is found that theparticle adhesion behavior and the internal distribution
depend on the transfer parameter of simulated structures.
Also, based on the difference of the pressure drop andthe ratio of particle adhesion on the surface by structure
characteristics, we made the filter characteristic map
which can be applied to design the optimal filter. In ourfuture study, we will try to clarify the actual phenomena
and to examine various filter structures. Moreover, it will
be necessary to compare with experimental value, so wewill conduct experiment in the future.
Acknowledgement: This research was supported by
Grant-in-Aid for Young Scientists (A) of the Ministry ofEducation, Culture, Sports, Science and Technology. Theauthor (Shinya Abe) is also grateful for the educational
program provided by the Global-Center of Excellence inNovel Carbon Resource Sciences, Kyushu University.
References

1.31)

1.22)

1.13)

1

uniform

0.9

non-uniform

0.8
00.2

0.4

0.6

Rate of surface adherent amount (As) [g/g]Fig. 11Filter characteristic map concerning the behaviorof particle adhesion (As: the particle adhesion
ratio on surface of filter and Tp: the ratio ofthe time until completely obstructed filter byparticle adhesion to the time of standard filter).

G. Inoue, T. Yoshimoto, Y. Matsukuma, M. Minemoto,
J Power Source, 175, 145 (2008).
J. T. Gostick and M.W. Fowler, J Power Source, 162, 228(2006).
T. Sera, K. Inoue, Mitsubishi Heavy Industry TechnicalReport, 33(1), 14 (1996).