Optimization of vane mist eliminators


Narimani, E.; Shahhoseini, S.

Applied Thermal Engineering 31(2-3): 188-193

2011


Vane mist eliminators are among the most effective devices to separate liquid droplets from a gas flow. Separation efficiency of these devices is largely dependent on the gas velocity, vane spacing and vane turning angles. In this study the efficiency of this type of mist eliminator has been investigated, using computational fluid dynamic (CFD). In addition, a prediction model of the separation efficiency was obtained based on the response surface methodology. The simulation results showed that there was a conceivable dependency of separation efficiency on the gas velocity and geometrical parameters of vanes. The optimal values of these parameters were determined in order to achieve the maximum separation efficiency.

Applied
Thermal
Engineering
31
(2011)
188-193
Contents
lists
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at
ScienceDirect
Applied
Thermal
Engineering
APPLIED
THERMAL
ENGINEERING
PI
,SEVIFP
journal
homepage:
www.elsevier.com/locate/apthermeng
Optimization
of
vane
mist
eliminators
Elhame
Narimani,
Shahrokh
Shahhoseini*
Simulation
and
Control
Research
Laboratory,
School
of
Chemical
Engineering,
Iran
University
of
Science
and
Technology,
P.O.
Box
16765-163,
Tehran,
Iran
ARTICLE INFO
ABSTRACT
Article
history:
Received
9
November
2009
Accepted
31
August
2010
Available
online
21
September
2010
Keywords:
Mist
eliminators
CFD
Separation
efficiency
Vane
Response
surface
method
Vane
mist
eliminators
are
among
the
most
effective
devices
to
separate
liquid
droplets
from
a
gas
flow.
Separation
efficiency
of
these
devices
is
largely
dependent
on
the
gas
velocity,
vane
spacing
and
vane
turning
angles.
In
this
study
the
efficiency
of
this
type
of
mist
eliminator
has
been
investigated,
using
computational
fluid
dynamic
(CFD).
In
addition,
a
prediction
model
of
the
separation
efficiency
was
obtained
based
on
the
response
surface
methodology.
The
simulation
results
showed
that
there
was
a
conceivable
dependency
of
separation
efficiency
on
the
gas
velocity
and
geometrical
parameters
of
vanes.
The
optimal
values
of
these
parameters
were
determined
in
order
to
achieve
the
maximum
separation
efficiency.
©
2010
Elsevier
Ltd.
All
rights
reserved.
1.
Introduction
Since
gas
liquid
content
could
upset
or
damage
the
equipments,
it
is
sometimes
necessary
to
remove
small
quantities
of
liquid
drops
from
the
gas
streams.
Vane
mist
eliminators
are
the
devices
that
can
effectively
remove
entrained
liquid
from
a
gas
flow,
usually
by
inertial
impingement.
In
these
eliminators,
the
wavy
vanes
(zigzag
shaped
plates)
cause
the
gas
to
move
in
a
zigzag
manner
between
them
as
shown
in
Fig.
1.
The
liquid
drops
cannot
follow
these
changes
in
the
direction
due
to
their
higher
inertia.
Thus
they
impinge
and
adhere
on
to
the
solid
surfaces.
When
the
amount
of
the
liquid
is
sufficiently
high,
it
forms
a
film,
which
drains
away
under
the
gravity.
In
the
case
of
vertical
vane
units,
where
the
gas
flows
upwards,
this
drainage
is
counter-
current
to
the
gas
flow.
If
the
gas
flows
horizontally
through
the
unit
the
drainage
is
perpendicular
to
the
gas
flow
[1
].
The
separa-
tion
efficiency
was
investigated
by
Claes
and
De
Bruyne
[2].
Recently,
some
researchers
have
conducted
several
studies
in
order
to
improve
the
performance
of
demisters
[1-9].
Numerical
and
experimental
behavior
of
the
droplet
in
the
gas
flow
has
been
studied
by
A.I.Josang
[9].
Response
surface
methodology
(RSM)
applies
a
set
of
statistical
and
mathematical
techniques
that
are
useful
for
designing,
devel-
oping,
improving
and
optimizing
the
process
under
study.
RSM
has
widely
been
used
in
the
field
of
chemical
engineering
to
study
the
yield
or
output
of
a
system
PK
In
this
study
the
optimization
analysis
of
demisters
in
wet
flue
gas
desulphurization
has
been
*
Corresponding
author.
Tel.:
+98
21
77240540-2701.
E-mail
address:
(S.
Shahhoseini).
1359-4311/$
see
front
matter
©
2010
Elsevier
Ltd.
All
rights
reserved.
doi:10.1016/j.applthermaleng.2010.08.031
performed
by
researchers
[11
].
Since
they
ignored
film
breakup,
their
results
showed
that
the
higher
velocity
caused
the
more
separation
efficiency.
However,
in
real
practice
higher
air
velocity
also
leads
to
more
film
breakup
causing
lower
separation
efficiency.
In
this
research,
film
breakup
has
also
been
included
into
the
process
model.
Consequently,
it
was
possible
to
find
the
optimal
conditions
of
a
system
of
multistage
vanes.
2.
CFD
simulation
CFD
simulation
is
a
suitable
technique
to
study
the
hydrody-
namics,
involved
in
the
separation
of
the
droplets
from
the
gas
flow.
Most
of
the
liquid
droplets
can
be
separated
from
the
gas
flow
in
the
first
vane
stage.
However,
due
to
some
droplet
producing
phenomena
in
this
process
some
new
fine
droplets
can
be
found
at
the
outlet
of
the
separator.
It
is
desirable
to
find
out
the
possible
mechanisms
for
this
secondary
droplet
generation
and
consider
their
effects
on
the
performance
of
the
separator.
The
mechanisms
can
be
classified
into
four
groups
representing
the
origin
of
the
new
droplets
as
given
below.
1)
Droplet—droplet
interaction
2)
Droplet
breakup
3)
Splashing
of
impinging
droplet
4)
Re-entrainment
from
liquid
film
Among
the
above
mechanisms
for
secondary
droplet
generation
the
breakup
of
the
droplets
by
their
impingement
on
the
liquid
film
and
re-entrainment
from
the
liquid
film
are
more
likely
to
occur.
The
constant
Weber
number
model
was
applied
to
take
film
E.
Narimani,
S.
Shahhoseini
/Applied
Thermal
Engineering
31
(2011)
188-193
189
First
vane
stage
Second
Third
Fourth
Table
'1
The
re-entrainment
limit
for
constant
We
number
model
[9].
Fate
of
ligament
We
>
1.2
Re-entrainment
We
<
1.2
Unchanged
Fig.
1.
Fluid
flow
in
between
the
vanes
of
a
mist
eliminator.
Yd
=
e
-(d/dr
(2)
breakup
into
the
account
[9].
In
this
model
the
breakup
of
the
droplets
caused
by
re-entrainment
from
liquid
film
can
be
esti-
mated
based
on
the
following
equation.
pg
ugDj
We
=
(1)
3a
g
where,
Di
is
as
shown
in
Fig.
2.
This
equation
was
used
to
explain
the
re-entrainment
from
a
ligament
on
the
deposited
water.
The
ligament
can
be
created
from
a
droplet
impact
or
shear.
The
size
of
the
ligament
was
assumed
to
be
the
same
as
that
of
the
hitting
droplet.
The
size
of
the
droplet
was
used
to
determine
whether
re-entrainment
occurs
or
not.
A
Weber
number
threshold
is
then
required.
The
value
of
the
critical
We
number
applied
in
this
study
was
the
same
as
that
reported
in
the
literature,
which
gives
Wecriucal
=
1.2
[9].
Wecritical
is
the
maximum
stable
droplet
size
in
a
turbulent
stream.
Table
1
shows
a
summary
for
the
re-entrainment
limit
in
the
particle
tracking
routine.
In
the
conditions
of
this
study,
the
Weber
number
of
the
drop-
lets
was
in
the
range
of
4-7,
in
which
film
breakup
occurs.
The
normal
distribution
of
droplet
diameter
can
be
determined
using
Rosin-Rammler
correlation
to
produce
droplets
with
the
average
diameter
of
60
gm.
If
the
size
distribution
is
of
the
Rosin-
-Rammler
type,
the
mass
fraction
of
the
droplets
for
which
the
diameter
is
greater
than
d
can
be
calculated
as
below.
—1>
Fig.
2.
An
impinging
droplet
causes
waves
on
the
surface
that
may
lead
to
torn
the
ligaments
off
[9].
Where,
d
is
the
mean
diameter
and
equal
to
60
gm.
The
minimal
diameter
is
10
gm
and
the
maximum
one
is
110
gm.
n
is
the
spread
parameter.
It
was
calculated
to
be
4.2,
using
the
following
equation.
Ln(-LnY
d
)
n
-
Ln
(d
/
d)
(
3
)
In
this
work
Eulerian-Lagrangian
approach
was
applied.
The
droplets
were
supposed
to
be
the
discrete
phase
and
the
air
was
assumed
to
be
the
continuous
phase.
2.1.
Discrete
phase
model
The
trajectory
of
a
discrete
phase
particle
was
predicted
by
integrating
the
force
balance
on
the
particle,
which
is
written
in
a
Lagrangian
reference
frame.
This
force
balance
equates
the
particle
inertia
with
the
forces
acting
on
the
particle
and
can
be
written
(for
the
x
direction)
as
[1]:
c
=
D
Up)
±
gx
(Pp
-
P)
Fx
tit
Pp
where,
u
is
the
fluid
phase
velocity,
u
p
is
the
particle
velocity,
u
is
the
molecular
viscosity
of
the
fluid,
p
is
the
fluid
density,
p
p
is
the
density
of
the
particle
and
4
is
the
particle
diameter.
Re
is
the
relative
Reynolds
number,
which
is
defined
as
[11]:
Re
-
pdpktp
-
u
(
5
)
where
F
x
is
an
additional
acceleration
(force/unit
particle
mass)
term,
FD
(u
1.1p)
is
the
drag
force
per
unit
particle
mass
and
FD
can
be
calculated
as
below
[11].
F
18a
C
D
Re
D
d
2
P
24
The
drag
coefficient,
CD,
can
be
computed
as
follows
[9].
24
b
3
Re
Rsph
p„,b2
+
CD
n
ne
sp
h
b4
e
sp
h
b
1
=
exp
(2.3288
-
6.45810
±
2.44860
2
)
b
2
=
0.0964
+
0.55650
b
3
=
exp
(4.905
-
13.89440
+
18.42220
2
-
10.25990
3
)
b
4
=
exp
(1.4681
+
12.25840
-
20.73220
2
+
15.88550
3
)
where,
cp
is
the
shape
factor
and
defined
as:
s
(4)
(6)
(7)
(8)
(9)
190
E
Narimani,
S.
Shahhoseini
/Applied
Thermal
Engineering
31
(2011)
188-193
Table
2
Operating
conditions
and
fluid
property
[12].
Item
Flow
Flow
pattern
P,
Pa
T
°C
p
g
,
kg
m
-3
Pd.
kg
In
3
Ag,
Pa
S
-1
Ad,
Pa
S
-1
cr
N
rn
-1
Experiment
condition
Air
water
Dispersed
flow
0.1E+06
20
1.2
9.98E+02
1.8E-05
9.98E-04
73E-01
where,
s
is
the
surface
area
of
a
sphere
having
the
same
volume
as
the
particle
and
S
is
the
actual
surface
area
of
the
particle.
The
Reynolds
number
Re
sp
h
was
computed
where
the
sphere
diameter
was
equal
to
s.
In
this
study
4)
=
1.
22.
Continuous
phase
model
Navier-stokes
and
K—E
equations
of
continuous
phase
are
described
as:
au
ay
—n
+
ax
ay
au au au
ap
[8
2
u
0
2
1
+
u+y
=
F
x
+
at
ax
ay
ax
Re
8x
4
8y
4
+
+
vL
=
Fx
"
arl
at
ax
ay
ay
Re
8x
4
ay
2
a a
ak
au.
au.
au.
(no
+
(uku\
_
a
[(
u
+
,
t)
-
+
u
+
_
at
-
1
/
ax
;
tr
k
ax
P"ax
ax
;
ax
i
r
(13)
a
a
1Lt
at
c
i
e
au
i
au
i
au
;
(Pe)+
(Peuk)
=
a
[
(A
+
)H+
iii
.—
k+d
at
ax
k
ax
k
tr
e
ax
k
ax
;
x
;
x
i
e
2
—L2
p
k
where,
C
A
=
0.09,
Cl
=
1.44,
C2
=
1.92,
ak
=
1.0,
o
f
=
13
and
A
t
is
turbulent
velocity.
Calculated
as
[11]:
C
A
ple
e
The
number
of
droplet
breakups
(breakup
parcels)
directly
depends
on
the
air
velocity.
A
leaner
equation
was
proposed
to
model
this
relationship
as
given
below.
Breakup
parcels
=
Ax11±B
(16)
where,
A
and
B
are
the
model
parameters
and
their
values
were
determined
by
fitting
the
equation
into
the
experimental
data.
The
values
of
A
and
B
were
computed
as
1.4163
and
5.4124
respectively.
23.
Simulation
assumptions
In
this
simulation
the
following
presumptions
are
assumed:
1.
The
width
of
the
vanes
is
big
enough
to
suppose
the
flow
is
two
dimensional.
2.
The
number
of
the
stages
is
increased
when
the
vane
turning
angle
decreases
in
order
to
keep
the
vane
length
constant.
3.
The
flow
in
between
the
vanes
is
incompressible.
2.4.
Boundary
conditions
The
inlet
boundary
condition
of
the
gas
phase
was
that
the
inlet
velocity
of
liquid
droplets
was
assumed
to
be
equal
to
the
gas
inlet
velocity.
The
outlet
condition
was
that
outlet
pressure
was
equal
to
the
atmospheric
pressure.
In
this
study,
the
gas
flow
with
liquid
droplets
between
the
vanes
was
simulated,
where
gas
velocity
and
wetness
fraction
were
3-5
m/s
and
0.089,
respectively.
The
simu-
lation
results
were
compared
with
some
reported
experimental
data,
reported
in
the
literature
[12].
Then
this
vane
plates
were
simulated
with
three
different
vane
angles
and
three
vane
spacing.
In
these
cases
the
separating
efficiency
was
computed
using
CFD
simulations.
In
the
next
stage,
the
response
surface
method
was
employed
to
find
the
optimal
conditions
of
the
vane,
using
these
CFD
simulation
results
of
separating
efficiencies.
The
operating
conditions
and
fluid
properties
used
in
these
simulations
are
summarized
in
Table
2.
It
is
assumed
that
the
droplets
with
a
given
diameter
of
Ddi
were
injected
at
the
inlet
and
it
is
possible
to
find
some
droplets
at
the
outlet
with
a
diameter
equal
to
or
smaller
than
Ddi.
Thus,
the
separating
efficiency
of
a
droplet
can
be
calculated
as
follows
[11
].
7
1
E
(mindo
f
=1
E
mi
i=
yi
ndi
=
Xi
2.5.
Model
validation
The
separation
efficiency
simulations
were
performed
for
different
velocities
between
3
and
9
m/s,
where
a
=
120
and
D
=
20
mm.
Fig.
3
shows
good
agreement
between
the
predicted
separation
efficiency
and
corresponding
experiment
data
[12].
It
indicates
that
the
higher
air
velocities
lead
to
the
greater
separation
efficiencies.
The
reason
is,
increasing
the
gas
velocity
would
bring
more
inertial
force
leading
to
more
rapid
changes
in
the
moving
direction
of
the
droplets,
causing
to
the
impingement
of
more
droplets
into
the
vane
wall.
0.98
0.96
0.94
0.92
0.9
0.88
0.86
0.84
0.82
0.8
3
4
5
6
7
8
Air
velocity,
m/s
Fig.
3.
A
comparison
between
simulated
and
experimental
efficiencies.
(10)
(12)
(14)
(15)
(17)
(18)
Sep
ara
t
ion
e
ffic
iency
cx
p
si
tTI
E.
Narimani,
S.
Shahhoseini
/Applied
Thermal
Engineering
31
(2011)
188-193
191
Table
3
Low
and
high
levels
of
the
factors.
Independent
variables
Coded
levels
—1
0
1
v
(m/s)
3
4
5
D
(mm)
20
30
40
(°)
60
90
120
2.6.
Response
surface
method
The
response
surface
method
was
applied
to
find
the
optimal
conditions
of
a
vane
mist
eliminator
in
terms
of
gas
velocity,
vane
spacing
and
vane
turning
angle
in
order
to
maximize
separation
efficiency.
The
response
surface
method
fits
a
polynomial,
as
given
in
equation
(19),
into
the
experimental
data
and
then
employs
the
polynomial
to
find
the
optimal
conditions
111].
k
k
Y
=
3
0
+
+
E
(3
i
X
i
E
+
e(X
i
,
X
2
.
.,X
k
)
(19)
i
=1
i=1
where,
Yis
the
response,
k
is
a
variable,
e
is
the
error
and
/3i,
/3i
and
h
are
the
unknown
parameters
in
the
second
order
polynomial
model.
Modeling
and
experimental
errors
are
two
sources
of
error
(e)
in
equation
(19).
Since
in
this
study
CFD
data
are
used
instead
of
experimental
data
the
error
(e)
is
only
due
to
the
weakness
of
fit.
A
three-factor,
three-level
central
composite
face-centered
design
(CCF)
was
used
to
determine
the
optimal
factors
of
separation
efficiency.
Three
independent
variables
were
selected
to
be
gas
velocity
(x1),
vane
spacing
(x2)
and
vane
angle
(x3).
A
total
of
15 different
combinations
(including
one
replicate
of
centre
point
that
was
signed
the
coded
value
of
0)
were
chosen
in
random
order
according
to
a
CCF
configuration
for
the
three
factors.
Several
CFD
simulations
were
carried
out
to
inspect
how
the
parameters
affect
the
vane
separation
efficiency.
The
coded
values
of
independent
variables
were
found
from
the
following
equation.
X
1
X
1
4
x1
1/2(X1H
Xu)
1
X2
X2
30
X2
1
/2(X2N
X2L)
10
2(
X3
90
3
1
/2
(X
3H
X
3L
)
30
Table
4
Central
composite
face-centered
design
with
three
independent
variables
(coded
variables).
RUN
X2
X3
1
—1
—1 —1
2
+1
—1 —1
3
—1
+1
—1
4
+1
+1
—1
5
—1
—1
+1
6
+1
—1
+1
7
—1
+1
+1
8
+1
+1
+1
9
—1
0
0
10
+1
0
0
11
0
—1
0
12
0
+1
0
13
0 0
—1
14
0 0
+1
15
0 0
0
Table
5
The
relation
between
vane
spacing,
separation
efficiency
and
pressure
drop.
D
(mm)
'1
,1P
(Pa)
20
8.62E-01
434E-02
30
6.8E-01
2.07E-02
40
633E-01
75-03
Each
independent
coded
variable
had
3
levels
of
—1,
0
and
+1.
In
Table
3
high
and
low
levels
of
these
three
factors
are
presented.
Table
4
shows
the
values
that
were
used
for
the
central
composite
face-centered
(CCF)
design.
3.
Results
and
discussion
The
results
of
Table
5
show
the
relations
among
vane
spacing,
separation
efficiency
and
pressure
drop.
They
were
produced
where
vane
angle
and
air
velocity
were
120°
and
3
m/s,
respec-
tively.
This
table
indicates declining
vane
spacing
raises
vane
separation
efficiency.
It
also
implies
that
the
lower
vane
spacing
gives
the
higher
pressure
drop.
Therefore,
the
highest
desirable
pressure
drop
is
first
to
be
determined
then
the
lowest
corre-
sponding
vane
spacing
can
be
used
as
a
constraint
of
the
optimization.
Table
6
shows
three
values
for
each
parameter
(gas
velocity,
vane
spacing
and
vane
angle)
and
corresponding
values
of
sepa-
ration
efficiency
from
CFD
simulation
results.
The
coefficients
of
equation
(19)
were
calculated
by
applying
multiple
regressions.
Tables
7
and
8
show
these
coefficients
for
the
uncoded
and
coded
factors.
The
uncoded
second
order
model
was
obtained
as
follows.
Y
=
1.036
0.1223(
1
+
0.0037X
2
+
0.00286X
3
+
0.01364
+
0.00001674
—0.0000132X3
+0.000175X
1
X2
+
0.000283X1
X3
0
.0000950X
2
X
3
(23)
R
2
is
the
coefficient
of
multiple
determinations
and
measures
the
proportion
of
the
variation
in
the
data
point
Yi,
which
is
explained
by
the
regression
model.
Ra
2
is
used
to
balance
the
cost
of
using
a
model
with
more
parameters
against
the
increase
in
R
2
.
In
this
study
R
2
is
99.18%
and
Ra
2
is
97.7%.
Ra
(n
1)R
2
K
n
—1
K
(24)
Ra
2
<
R
2
where,
k
is
the
number
of
regression
parameters
in
the
model
and
n
is
the
number
of
data
points.
Table
6
CFD
simulation
results
for
separation
efficiency.
RUN
x
1
x2
X
3
Y*10
1
3
20
60
9.41
2
5
20
60
9.65
3
3
40
60
935
4
5
40
60
955
5
3
20
120
9.12
6
5
20
120
959
7
3
40
120
7.81
8
5
40
120
8.46
9
3
30
90
9.13
10
5
30
90
933
11
4
20 90
938
12
4
40
90
8.84
13
4
30
60
932
14
4
30
120
8.63
15
4
30
90
9.05
(20)
(21)
(22)
192
E
Narimani,
S.
Shahhoseini
/Applied
Thermal
Engineering
31
(2011)
188-193
Table
7
Estimated
regression
coefficients
and
corresponding
separation
efficiencies
for
uncoded
factors.
Term
Coefficient
Standard
error
T
statistic
P
level
Constant
1.036
8327E-02
12.442
0.0
x
1
-0.122
0.039
-3.123
0.026
x
2
3.709E-03 3.118E-03
1.189
0.287
x
3
2.860E-03
1.039E-03
2.751
0.040
XIX2
1.750E-04
2.656E-04
0.658
0539
XiX
3
2.833E-04
8.855E-05
3.199
0.024
X
2
X
3
-9.500e-05
8.855E-06
-10.728
0.000
x
1
x
1
1366E-02
4.686E-03
2.917
0.033
X2X2
1.666E-05
4.686E-05
0356
0.736
X
3
X
3
-1315E-05
5.206E-06
-2.525
0.053
Table
8
Estimated
regression
coefficients
and
corresponding
separation
efficiencies
for
coded
factors.
Term
Coefficient
Standard
error
T
statistic
P
level
Constant
0.908
4.039E-03
224.943
0.0
x
1
0.016
2376E-03
7.407
0.000
x2
-0.031
2376E-03
-13.215
0.0000
X3
-0.037
2376E-03
-15.446
0.0000
xix2
1.749E-03
2.656E-03
0.659
0.539
X1X3
8.49E-03
2.657E-03
3.199
0.024
X2X3
-0.0285
2.657E-03
-10.728
0.000
x
1
x
1
1367E-02
4.686E-03
2.917
0.033
x2x2
1.667E-03
4.686E-03
0356
0.736
X3X3
-1.183E-02
4.686E-03
-2.526
0.053
The
coded
factors
are
dimensionless
variables.
The
coefficients
of
equation
(19)
for
coded
factors
were
estimated
by
the
means
of
a
least
squares
method.
The
coded
second
order
model
was
obtained
as
follows.
Y
=
0.908
+
0.0176x
1
-
0.0314x
2
-
0.0367x
3
+0.0137x1
+0.001674
-
0.01184
+0.00175X12(2
0.00849x
1
x
3
-
0.0285x
2
x
3
(25)
Given
the
values
of
vane
spacing,
vane
angle
and
air
velocity,
vane
efficiency
can
be
calculated
from
equation
(25).
Each
of
these
parameters
has
a
dual
effect
on
the
performance
of
the
separator.
Vane
spacing
is
a
crucial
variable
to
keep
high
separation
efficiency
and
maintain
the
demister
system
stable.
On
one
hand,
too
small
vane
spacing
leads
to
too
much
pressure
drop
and
energy
consumption
for
pumping
the
gas.
On
the
other
hand,
if
the
vane
spacing
is
too
large,
the
separation
efficiency
drops
due
to
the
large
moving
area
of
the
droplets.
A
large
value
of
air
velocity
leads
to
a
high
inertial
force
that
in
turn
causes
rapid
changes
in
the
moving
direction
of
the
droplets,
forcing
them
to
crash
harder
into
the
vane
walls
and
resulting
in
high
separation
efficiency.
However,
higher
air
velocities
cause
more
significant
liquid
film
breakup
leading
to
less
separation
efficiency.
A
small
vane
angle
results
in
a
large
centrifugal
force
of
the
droplets
at
the
bends
of
the
vanes,
which
results
in
more
separation
efficiency.
Whereas,
too
small
vane
angles
means
there
would
be
less
chance
for
the
droplets
to
move
around
the
bend
walls
leading
to
less
separation
rate.
The
CFD
simulation
results
revealed
that
if
vane
angle
is
smaller
than
its
optimal
value
the
gas
flow
cannot
move
well
inside
the
bends,
causing
a
low
separation
rate.
4.
Conclusions
In
this
study
the
separation
efficiency
of
liquid
droplet
by
way
plate
separators
was
simulated
and
compared
with
the
experi-
mental
data.
It
was
assumed
that
liquid
droplet
breakup
by
impingement
of
liquid
film
was
the
most
important
mechanism
for
the
generation
of
the
secondary
droplets
under
the
operating
conditions.
Since
CFD
simulation
results
were
in
good
agreement
with
the
experimental
data,
the
CFD
results
were
applied
in
order
to
investigate
the
influence
of
gas
velocity,
vane
spacing
and
vane
turning
angle
on
the
separation
efficiency
based
on
a
response
surface
method.
This
investigation
resulted
in
a
mathematical
model
that
in
turn
was
employed
to
find
the
optimal
conditions
for
maximum
separation
efficiency
of
the
demisters.
The
results
revealed
that
in
the
20
mm
of
vane
spacing
the
highest
separation
efficiency
could
be
achieved
when
the
air
velocity
and
vane
angle
were
5
m/s
and
60°,
respectively.
Nomenclature
Vane
angle,
°(degree)
Drag
coefficient,
Dimensionless
Ligament
diameter,
mm
Vane
spacing,
mm
Particle
diameter,
mm
Diameter
of
ith
droplet
with
d
diameter,
mm
Pressure
dropt,
Pa
Mean
diameter,
nm
Additional
acceleration,
Force
Unit
partical
mass
Drag
force,
Force.
Unit
partical
mass
Mass
of
droplets
with
y;
mass
fraction,
kg
Gas
viscosity,
Pa
s
-1
Molecular
viscosity,
Pa
s
-1
Spread
parameter,
Dimensionless
Relative
Reynolds
number,
Dimensionless
Droplet
density,
Kg
M
-3
Gas
density,
Kg
M
-3
Fluid
density,
Kg
m
-3
Droplet
density,
Kg
M
-3
Surface
Area,
m
2
Air
velocity,
m
s
-1
Particle
velocity,
m
s
-1
Gas
flow
velocity,
m
Air
velocity,
m
Weber
number,
Dimensionless
Critical
Weber
number,
Dimensionless
Dimensionless
variables,
Dimensionless
uncoded
variables,
-
Mean
value
of
uncoded
variables,
-
The
high
level
of
the
ith
factor,
-
The
low
level
of
the
ith
factor,
-
Coded
variable,
Dimensionless
Mass
fraction
of
injected
droplets,
Dimensionless
Response,
Dimensionless
Mass
fraction
of
separated
droplets,
Dimensionless
Vane
separation
efficiency,
Dimensionless
Surface
tension,
N.m-1
Shape
factor,
Dimensionless
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