Numerical Study on the Treatment of Micro Fiber Particles with
Atmospheric Microwave Air Plasma
A. Averroes and H. Sekiguchi
Department of Chemical Engineering, Tokyo Institute of Technology, Tokyo, Japan
Abstract: The atmospheric microwave air plasma has been suggested to treat
airborne asbestos released from asbestos disposal facility. In previous study, the
treatment of asbestos alike ceramic fiber and stainless fiber materials with
atmospheric microwave air plasma was conducted. The scanning electron
microscope (SEM) showed the spheroidization of some treated particles. This
study presents the numerical calculation of velocity and temperature field around
microwave plasma torch. Then, the particle trajectory analysis was applied to
examine the melting condition of the treated particles. The calculation was
carried out by using the finite element method based commercial software with
k-ɛ turbulence as the model of velocity field. The numerical result was compared
with the experiment results.
Keywords: Airborne asbestos, Microwave air plasma, Atmospheric nonequilibrium plasma, Spheroidization, Heat transfer coefficient
1. Introduction
Recently, asbestos becomes a serious problem due to
its potential of causing some diseases like lung
cancer, asbestosis, mesothelioma, and diffuse pleural
thickening.1 Asbestos is needle–shaped, lightweight,
and so easily inhaled into the lung, becoming the
trigger of the diseases as accumulated there.
Especially airborne asbestos released from buildings
when removing asbestos containing material or from
asbestos disposal facility must be treated properly.
Microwave plasma is a discharge with microwave as
source energy. It has some advantageous
characteristics such as electrode-less discharge, high
gas temperature (about 3000 ℃ ) and compact in
size.2 The application of this high gas temperature
will set off melting, followed by the spheroidization
and or composition change of asbestos. Therefore,
we suggest the treatment of airborne asbestos
contained in exhaust gas of asbestos disposal facility
with microwave air plasma.
In the previous study, we have already succeeded in
spheroidizing of asbestos alike ceramic fiber with
atmospheric microwave plasma.3 In this study,
numerical calculation of the velocity the and
temperature field around microwave plasma torch
has been carried out. It was continued by particle
tracking through microwave induced air plasma to
evaluate the melting condition of each particle.
2. Experiments
2.1 The microwave air plasma treatment
In order to generate air plasma, air streams were fed
tangentially through a nozzle into quartz tube (I.D.
9.5 mm). A microwave power (2.45GHz, IDX Co.,
Ltd.) was coupled to the gas as it passed through a
waveguide. A detailed description of experimental
apparatus was presented elsewhere.3 Raw particles
were fed into air plasma from the top of the tube
constantly by using particle feeder and air as carrier
gas. Input power and air flow rate were varied as
parameters as shown in Table 1. The particles
subjected to plasma treatment were micro fiber
particles listed in Table 2 together with their
characteristics.
2.2 The two dimensional analysis of particle
100~200 samples of both raw and treated particles
were captured by SEM, then the image analysis
software (Scion Image) was used to measure the area
of projected particle (S), also the major axis (L) and
the minor axis (W) of approximate ellipse of
projected particle.
Table 2 Characteristics of microfibers
Table 1 Experimental conditions
Reaction tube (mm)
Reaction branch (mm)
Particle inlet branch (mm)
Heat source (mm)
Air flow rate (L/min)
Carrier gas flow rate (L/min)
Input power (W)
I.D=9.5,O.D=11.5,L=300
I.D=2, O.D=4, L=20
I.D=4, O.D=6
∅ 2 Length=150
8.1, 11.4, 14.1
3.5
800, 1000, 1200
The diameter of equivalent circular area (Da), and
the aspect ratio (AR) were used as particle shape
indices (eq.1 and 2) with initial values as shown in
Table 2. Da indicates the diameter of a circle with
the same area as projected particle.
Da = 2
AR =
S
π
Type of Fiber Particle：
IBI Wool (IW)
SMF300UE (SMF)
Fibermax (FM)
Particle density, ρp (kg/m3)
Melting point, Tm (K)
Fiber thickness (µm)
Fiber average length (µm)
Da [µm]
AR [-]
Al2O3=0.46, SiO2=0.51
Fe=0.83, Cr=0.16,
Ferritic Stainless Steel =0.01
Al2O3=0.72, SiO2=0.28
IW=2700，SMF=7700，FM=2900
IW=2033，SMF=1742，FM=2143
IW=1.8-3，SMF=5-10，FM=4-6
IW=34，SMF=15-50，FM=48
IW= 16.7，SMF= 25.0，FM= 17.4
IW= 0.32，SMF= 0.43，FM= 0.19
(1)
W (2)
L
3. Numerical modeling
The numerical simulations were carried out by
COMSOL Multiphysics 3.5a, a commercial finite
element analysis based software. The calculation
domain was a quartz tube and the fluid inside
including plasma plume as illustrated in fig. 1. The
detailed experimental conditions for the simulation
are shown in Table 1. The model was made by
assuming that: (i) the plasma plume is an ellipsoidal
shape heat source, (ii) the efficiency of plasma
generation is 100%, (iii) the plasma is in a stable
condition, (iv) overall flow is turbulent (Re>5,000),
(v) gas is a Newtonian fluid.
3.1 Numerical calculation of velocity field
The k-ɛ Turbulence model of momentum transport
module was used to calculate the flow field.



ρ (u ⋅ ∇ )u = ∇ ⋅ − pI + (η + ηT ) ∇u + (∇u )T −

2
(∇ ⋅ u )I  − 2 ρkI  + F
3
 3

∇ ⋅ (ρu ) = 0
(5)

η
ρu ⋅ ∇k = ∇ ⋅ η + T
σk


ρu ⋅ ∇ε = ∇ ⋅ η +

where,
(4)
ηT
σε
 
2 ρk
∇k  + ηT P(u ) −
∇ ⋅ u − ρε
3

 
  Cε 1ε
∇ε  +
k
 
(
2 ρk
ε2


ηT P(u ) − 3 ∇ ⋅ u  − Cε 2 ρ k


P(u ) = ∇u : ∇u + (∇u )
ηT = ρC µ
ε2
k
T
)
2
2
− (∇ ⋅ u )
3
Figure 1. 3D geometric domain of numerical calculation
Eq. (4) is a vector equation of the conservation of
momentum. Eq. (5) is the continuity equation and
represents the conversion of mass. Eq. (6) and (7) is
the transport equation for the turbulence kinetic
energy k and the dissipation rate of turbulence
energy ɛ, respectively. Eq. (9) is equation turbulent
viscosity for k-ɛ Turbulence model. u is the velocity
field,ηis the dynamic viscosity, F is a volume force
field such as gravity, C µ , Cε 1 , Cε 2 , σ k , σ ε are
constants for turbulence model with their values are
0.09, 1.44, 1.92, 1, 1.3, respectively.
3.2 Numerical calculation of temperature field
(6)
(7)
The conduction and convection model include the
energy balance (eq.10) and the turbulent thermal
conductivity equation (eq.11) was solved.
∇ ⋅ (− (k + kT )∇T ) = Q − ρC pu ⋅ ∇T
(10)
(8)
kT = C pηT
(11)
(9)
here, Q indicates the heat source.
3.3 Numerical calculation of particle trajectory
[
F = πrs2 ρ p (u − u p ) 1.849(Re p )
2
− 0.31
+ 0.293(Re p )
]
0.06 3.45
(12)
0.8 kW
1.0 kW
1.2 kW
3000
Temperature [K]
The Khan-Richardson force model was used to track
the particles fed into the quartz tube. This model is
used to calculate the force (see eq.12) on a sphere
particle under viscous conditions and a large
dynamic range of Rep (up to approximately 105).4
Particle tracking was carried out by setting 185
points at z=30mm of particles introduction part.
4000
2000
1000
4. Results and Discussion
4.1 The temperature distribution of plasma
0
Fig. 2 shows the effects of input power on the
temperature distribution. The temperature was
increased by the increase of input power. And fig. 3
indicates that the temperature became higher as swirl
air flow rate decreased. The jagged curve observed
here is suggested due to the use of turbulence model.
(12)
where Tf is the temperature of fluid, T0 is initial
temperature of the particle, and h is the heat transfer
coefficient of the fluid calculated by using the
Churchill-Bernstein correlation.5 If Tp reached Tm,
the particle is considered as melted. And the ratio
between the remaining heat obtained by particle ( λ ′ ,
eq. (14)) and heat required to completely melt ( λ )
can be used to decide the melting condition (see fig.
4). Based on this algorithm, the melting condition of
trajectory particle was calculated and evaluated.
4h(T f − Tm )t 2
ρ p Dp
0.3
Figure 2. Effects of input power on temperature along the center of
quartz tube (x=0, y=0) at swirl air flow rate=11.4 L/min.
4000
(14)
Temperature [K]
In this section, the heat transfer between air plasma
and the particles was considered. The melting time
of particles can be divided into the time required to
raise the temperature of particles to its melting point
(t1) and the time required by particles to completely
melt at melting point (t2). We assumed that there is
no temperature distribution inside fibers, all particles
are cylindrical, and all fibers are converted into
sphere as they melted. Thus, the temperature history
of fiber can be calculated as follows:
λ′ =
0.2
(0.3–z) [m]
8.1 L/min
11.4L/min
14.1L/min
3000
4.2 The temperature history of particle
 − ht1 
T p = T f − (T f − T0 )exp 

 ρ p D p C p 
0.1
2000
1000
0
0.1
0.2
0.3
(0.3–z) [m]
Figure 3. Effects of swirl air flow rate on temperature distribution along
the center of quartz tube (x=0, y=0) at input power=1.0kW.
Figure 4. Evaluation of melting condition
4.3 Effects of input power on melting condition
Fig. 5 shows the effects of input power on melting
condition. The melting condition became better by
increasing input power which was comparable with
SEM results in fig.6. Some coordinate positions of
particle fed into the plasma tended to have good
melting condition regardless of type of particle.
IW
IW
SMF
SMF
FM
FM
Figure 5. Particle trajectory (from z=30mm) and melting condition at
swirl air flow rate=11.4L/min for input power 0.8, 1.0, and 1.2 kW from
left to right ( =unmelted,
=partial melt, =complete melt)
Figure 7. Particle trajectory (from z=30mm) and melting condition at
input power=1kW for swirl air flow rate of 8.1, 11.4, and 14.1 L/min
from left to right ( =unmelted, =partial melt, =complete melt)
Figure 8. The Effects of swirl air flow rate on ∆AR at input power=1kW
Figure 6. The SEM photos of micro fiber particle before treatment (left),
8.0kW (center), and 1.2kW (right) for IW, SMF, and FM (up-bottom).
4.4 Effects of swirl air flow rate on melting
condition
Fig. 7 shows the effects of the swirl air flow rate on
melting condition. The melting condition of IW and
FM seemed to have a maximum at 11.4L/min as the
swirl air flow rate increased. Meanwhile, SMF
tended to get worse. This trend was quite similar to
the experiment results in fig. 8 except for FM.
5. Conclusion
The treatment of micro fiber particle was modeled
by commercial finite element method software. The
velocity and the temperature field were calculated
and followed by the particle trajectory calculation.
The results showed the increase of melting condition
by input power. However, the swirl air flow rate
tended to decrease the melting condition. These
solutions show a consistency with the SEM analysis
of practical plasma treatment to an extent.
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