Isolation of AMF by wet sieving and decantation method pptx
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Workshop presentations l_bworkshop_reis
1. Pinning and facetting in lattice Boltzmann
simulations
Tim Reis
Oxford Centre for Collaborative Applied Mathematics
Mathematical Institute
University of Oxford
OCCAM/ICFD Lattice Boltzmann Workshop, September
2010
2. Recolouring in multiphase lattice Boltzmann models
Lattice Boltzmann models for continuum multiphase ļ¬ows use a
ācolour ļ¬eld" to represent different phases.
A recolouring algorithm is needed to encourage phase segregation
and maintain narrow boundaries between ļ¬uids.
Maximising the work done against the colour gradient predicts sharp
interfaces but causes spurious behaviour:
3. Other recolouring algorithms
Latva-Kokko and Rothman (2005) offer an alternative redistribution:
fk
i =
ā¢k
ā¢
f0
i Ā±
ā¢r
ā¢b
ā¢2
f
(0)
i cos āµ
See also DāOrtona et al. (1995), Tƶlke et al. (2002)
4. Motivation
ā¢ Multiphase LBEs are prone to lattice pinning and facetting
(Latva-Kokko & Rothman (2005), Halliday et al. (2006)).
ā¢ Similar difļ¬culties arise in combustion (Colella (1986), Pember
(1993)).
ā¢ Spurious phenomena associated with stiff source terms
investigated by LeVeque & Yee (1990).
ā¢ Unphysical behaviour can be corrected with a random projection
method (Bao & Jin (2000)).
ā¢ LB formulation of these models can shed light on pinning and
facetting.
5. Phase ļ¬elds, pinning and facetting
Two types of particles: red & blue.
Scalar ļ¬eld , the ācolourā
ā” 1 in red phase (oil)
ā” 0 in blue phase (water)
Diffuse interfaces marked by
transitions from ā” 1 to ā” 0.
@t + u Ā· r = S( ).
6. Model problem for propagating sharp interfaces
@
@t
+ u
@
@x
= S( ) =
1
T
1 1
2
TS( ) = 1 1
2
d
dt = S( )
ā The numerical results presented above indicate a disturbing feature
of this problem ā it is possible to compute perfectly reasonable results
that are stable and free from oscillations and yet are completely
incorrect. Needless to say, this can be misleading.ā
LeVeque & Yee (1990)
7. Lattice Boltzmann Implementation
Suppose =
P
i fi and postulate the discrete Boltzmann equation:
@t fi + ci @x fi =
1
ā§
ā£
fi f
(0)
i
ā
+ Ri .
With the following equilibrium function and discrete source term :
f
(0)
i = Wi (1 + ci u),
Ri = 1
2 S( )(1 + ci u);
the Chapman-Enskog expansion yields the
advection-reaction-diffusion equation:
@
@t
+ u
@
@x
= S( ) + ā§(1 u2
)
@2
@x2
.
8. Reduction to Fully Discrete Form
The previous discrete Boltzmann equation can be written as
@t fi + ci @x fi = ā¦i
Integrate along a characteristic for time t:
fi (x + ci t, t + t) fi (x, t) =
Z t
0
ā¦i (x + ci s, t + s) ds,
and approximate the integral by the trapezium rule:
fi (x +ci t, t+ t) fi (x, t) =
t
2
ā£
ā¦i (x +ci t, t+ t)
+ ā¦i (x, t)
ā
+O t3
.
This is an implicit system.
9. Change of Variables
To obtain a second order explicit LBE at time t + t deļ¬ne
fi (x0
, t0
) = fi (x0
, t0
)
t
2ā§
ā£
fi (x0
, t) f
(0)
i (x0
, t)
ā t
2
Ri (x0
, t)
The new algorithm is
fi (x + ci t , t + t) fi (x, t)
=
t
ā§ + t/2
ā£
fi (x, t) f
(0)
i (x, t)
ā
+
ā§ t
ā§ + t/2
Ri (x, t),
However, we need to ļ¬nd in order to compute f
(0)
i and Ri .
10. Reconstruction of
The source term does not conserve :
ĀÆ =
X
i
fi =
X
i
ļ£æ
fi
t
2ā§
ā£
fi f
(0)
i
ā t
2
Ri
= +
t
2T
1 1
2 = N( ).
We can reconstruct by solving the nonlinear equation N( ) = ĀÆ
using Newtonās method:
!
N( ) ĀÆ
N0( )
,
Note that N( ) = + O( t/T).
11. Lengthscale of Transition
The diffusive extension of LeVeque and Yeeās model is
@
@t
+ u
@
@x
= S( ) + ļ£æ
@2
@x2
Solving the ODE
0 = S( ) + ļ£æ
@2
@x2
gives us the interface proļ¬le
(x) = (1 + exp x/L)
1
,
where L =
p
2ā§T x is the lengthscale of transition
13. Pinning as a result of sharpening
Numerical solutions for ā§/T = 1 (left) and ā§/T = 50 (right).
14. Conservation Trouble
In the 2D case the circular region shrinks and eventually disappears:
This is due to the curvature of the interface:
We ļ¬nd c that satisļ¬es
M =
Z
ā¦
S( , c)dā¦.
15. Facetting with a D2Q9 Model
Propagating circular patch when ā§/T = 10. Notice the beginnings of
a facet on the leading edge . . .
When ā§/T = 50 the facetting is severe . . .
16. Recap: Model problem for propagating sharp
interfaces (LeVeque & Yee 1990)
@
@t
+ u
@
@x
= S( ) =
1
T
1 1
2
Usually implemented as separate advection and sharpening steps.
@
@t + u @
@x = 0
@
@t
= S( )
17. The Random Projection Method
The LeVeque & Yee source term is effectively the deterministic
projection
SD( ) : (x, t + t) =
(
1 if 0
(x, t) > 1/2,
0 if 0
(x, t) ļ£æ 1/2.
Bao & Jin (2000) replace the critical c = 1/2 with a uniformly
distributed random variable
(n)
c :
SR( ) : (x, t + t) =
(
1 if 0
(x, t) >
(n)
c ,
0 if 0
(x, t) ļ£æ
(n)
c .
@
@t
+ u Ā· r =
1
T
1 (n)
c .
18. Comparison of Propagation Speed (1D)
The speed of the interface is dictated by the ratio of timescales, ā§
T .
19. Comparing the Radii of the Patches at t = 0.4
The Random Projection model preserves the circular shape at
ā§/T = 10
and is clearly superior to the LeVeque model when ā§/T = 30
20. A non-smooth problem: ā§
T = 30
An initial square patch fails to collapse to a circle when using a
deterministice volume preserving threshold . . .
. . . but behaves correctly when we introduce the van der Corput
sequence:
21. Topological changes: ā§
T = 30
An initial square patch fails to collapse to a circle when using a
deterministice volume preserving threshold . . .
. . . but behaves correctly when we introduce the van der Corput
sequence:
22. A conservative scheme
If we assume L =
p
2ā§T x then
@
@n
= r Ā· n = |r | =
(1 )
L
,
@2
@n2
=
(r Ā· r)|r |
|r |
=
(1 )(1
2 )
L2
.
We can now show that a DBE of the form
@fi
@t
+ ci
@fi
@x
=
1
ā§
ā£
fi f
(0)
i
ā
+ Wi
(1 )
L
ci Ā· n
furnishes
@
@t
+ u
@
@x
= ā§(1 u2
)r2
+ ā§r2 (1 )(1
2 )
T
in the macroscopic limit.
24. Conclusion
ā¢ We have studied the combination of advection and sharpening of
the phase ļ¬eld that commonly arises in lattice Boltzmann models
for multiphase ļ¬ows.
ā¢ Overly sharp phase boundaries can become pinned to the
lattice. This has been shown to be a purely kinematic effect.
ā¢ Replacing the threshold with a uniformly distributed
pseudo-random variable allows us to predict the correct
propagation speed at very sharp boundaries (ā§/T > 100).
ā¢ The onset of facetting is signifļ¬canly delayed if we introduce a
random term into the volume-preserving multi-dimensional
extension.