Homogenization of reactive flows in porous media · 2012-10-15 · Homogenization of reactive...
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Homogenization of reactive flows inporous media
G. Allaire ∗, H. Hutridurga ∗
13-October-2010
∗Centre de Mathematiques Appliquees, CNRS UMR 7641, Ecole Polytech-nique, 91128 Palaiseau, France
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Outline
* Why study Reactive Flows in porous media?
* Periodic porous media and Model description
* Two-scale Expansion with Drift Method
* Numerical Study with FreeFem++
* Conclusions
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Why study Reactive Flows in porous media?
* Oil reservoir simulation (Enhanced Recovery Mechanisms)
* CO2 storage (Natural Gas Extraction)
* Geothermal energy extraction
* Underground coal gasification
* Stockage of Nuclear Wastes
* Ground water contaminant transport (Drinking and Irrigation)
* Soil Chemistry (Movement of moisture, nutrients, pollutants in soil)
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Unbounded periodic porous media
Let ε > 0 represents the microscale of the porous medium
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Unbounded periodic porous media
Let ε > 0 represents the microscale of the porous medium
Y = [0, 1]n
Y = Y 0 ∪ Σ0 s.t Y 0 ∩ Σ0 = ∅Y 0 fluid partΣ0 solid part
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Unbounded periodic porous media
Let ε > 0 represents the microscale of the porous medium
Y = [0, 1]n
Y = Y 0 ∪ Σ0 s.t Y 0 ∩ Σ0 = ∅Y 0 fluid partΣ0 solid part
Y εi = [0, ε]n
Y εi = (Y 0
i )ε ∪ (Σ0
i )ε
(Y 0
i )ε fluid part
(Σ0
i )ε solid part
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Unbounded periodic porous media
Let ε > 0 represents the microscale of the porous medium
Y = [0, 1]n
Y = Y 0 ∪ Σ0 s.t Y 0 ∩ Σ0 = ∅Y 0 fluid partΣ0 solid part
Y εi = [0, ε]n
Y εi = (Y 0
i )ε ∪ (Σ0
i )ε
(Y 0
i )ε fluid part
(Σ0
i )ε solid part
Ωε = Rn \ ∪i∈Z(Σ
0
i )ε = R
n∩i∈Z(Y0
i )ε
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Unbounded periodic porous media
Let ε > 0 represents the microscale of the porous medium
Y = [0, 1]n
Y = Y 0 ∪ Σ0 s.t Y 0 ∩ Σ0 = ∅Y 0 fluid partΣ0 solid part
Y εi = [0, ε]n
Y εi = (Y 0
i )ε ∪ (Σ0
i )ε
(Y 0
i )ε fluid part
(Σ0
i )ε solid part
Ωε = Rn \ ∪i∈Z(Σ
0
i )ε = R
n∩i∈Z(Y0
i )ε
Assumptions:Σ0 smooth, connected set strictly included in Y or forms a connected setin R
n by Y-periodicity.Ωε smooth, connected set in R
n
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2-D schematics
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2-D schematic of an unbounded porous media
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Model Description
We intend to study the Diffusive Transort of the solute
particles transported by a stationary incompressible viscous
flow in presence of a reaction through a porous medium.
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Model Description
We intend to study the Diffusive Transort of the solute
particles transported by a stationary incompressible viscous
flow in presence of a reaction through a porous medium.
Apart from the convection and diffusion in the bulk, we have considered
surface convection and surface diffusion on the pore surfaces.
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Model Description
We intend to study the Diffusive Transort of the solute
particles transported by a stationary incompressible viscous
flow in presence of a reaction through a porous medium.
Apart from the convection and diffusion in the bulk, we have considered
surface convection and surface diffusion on the pore surfaces.
For simplicity, we study Reactive Transport of a single solute.
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Model Description
We intend to study the Diffusive Transort of the solute
particles transported by a stationary incompressible viscous
flow in presence of a reaction through a porous medium.
Apart from the convection and diffusion in the bulk, we have considered
surface convection and surface diffusion on the pore surfaces.
For simplicity, we study Reactive Transport of a single solute.
Also, we assume that the reactive interactions are present only on
the pore surfaces (Linear Adsorption).
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Model Description contd.
The model is described as follows:
∂tuε +1
εbε · ∇xuε − divx(Dε∇xuε) = 0 in (0, T )× Ωε
uε(0, x) = u0(x), x ∈ Ωε
∂tvε +1
εbSε · ∇S
xvε − divSx (DSε ∇
Sxvε) =
1
ε2κ
(
uε −1
Kvε
)
= −1
εDε∇xuε · γ on (0, T )× ∂Ωε
vε(0, x) = v0(x), x ∈ ∂Ωε
(1)
uε(t, x) respresents the concentration of the solute in the bulk.
vε(t, x) represents the concentration of the solute on the pore surfaces.
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model description
κ Rate constantK Linear adsorption eq. const.
x Macroscopic variable y = xε
Microscopic variable
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model description
κ Rate constantK Linear adsorption eq. const.
x Macroscopic variable y = xε
Microscopic variable
γ(y) outward normalG(y) = Id− γ(y)⊗ γ(y) projection matrix∇S
xv = G∇xv tangential gradientdivSxΨ = divx(GΨ) tangential divergence
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model description
κ Rate constantK Linear adsorption eq. const.
x Macroscopic variable y = xε
Microscopic variable
γ(y) outward normalG(y) = Id− γ(y)⊗ γ(y) projection matrix∇S
xv = G∇xv tangential gradientdivSxΨ = divx(GΨ) tangential divergence
Dε(x) = D(xε) Periodic DS
ε (x) = DS(xε) Periodic symmetric
symmetric coercive diffusion coercive surface diffusion
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model description
κ Rate constantK Linear adsorption eq. const.
x Macroscopic variable y = xε
Microscopic variable
γ(y) outward normalG(y) = Id− γ(y)⊗ γ(y) projection matrix∇S
xv = G∇xv tangential gradientdivSxΨ = divx(GΨ) tangential divergence
Dε(x) = D(xε) Periodic DS
ε (x) = DS(xε) Periodic symmetric
symmetric coercive diffusion coercive surface diffusion
bε(x) = b(
xε
)
Stationary bSε (x) = bS(xε) Stationary
incompressible periodic flow incompressible periodic flowdivyb = 0 in Y 0 divSy b
S = 0 on ∂Σ0
b · γ = 0 on ∂Σ0
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Main Result
Theorem 1 The solution (uε, vε) of (1) satisfies
uε(t, x) ≈ u0(t, x−b∗
εt) and vε(t, x) ≈ Ku0(t, x−
b∗
εt)
with the effective drift
b∗ =
∫
Y 0
b(y) dy +K∫
∂Σ0
bS(y) dσ(y)
|Y 0|+K|∂Σ0|n−1
and u0 the solution of the homogenized problem
Kd ∂tu0 = divx (A∗∇xu0) in (0, T )× R
n
Kd u0(0, x) = |Y 0|u0(x) + |∂Σ0|n−1v0(x), x ∈ R
n
Where, Kd = |Y 0|+K|∂Σ0|n−1, the dispersion tensor A∗ will bedescribed later.
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Two-scale Asymptotic Expansion
The usual Two-scale Expansion method suggests us to
• Take the ansatz for uε(t, x) and vε(t, x) in slow and fast variables as
uε =∞∑
i=0
εiui
(
t, x,x
ε
)
and vε =∞∑
i=0
εivi
(
t, x,x
ε
)
• Plug-in the two asymptotic expansions in (1).
• Identify the co-efficients of identical powers of ε and get a cascade ofequations.
• solve those system of equations to arrive at the homogenizedequation.
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Two-scale Asymptotic Expansion
The usual Two-scale Expansion method suggests us to
• Take the ansatz for uε(t, x) and vε(t, x) in slow and fast variables as
uε =∞∑
i=0
εiui
(
t, x,x
ε
)
and vε =∞∑
i=0
εivi
(
t, x,x
ε
)
• Plug-in the two asymptotic expansions in (1).
• Identify the co-efficients of identical powers of ε and get a cascade ofequations.
• solve those system of equations to arrive at the homogenizedequation.
• Convection term in microscale results in strong convection termdominating the diffusion. So, we cannot expect to prove theconvergence of uε(t, x) in a fixed spatial frame x but in a movingframe x+ b∗t
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Two-scale Asymptotic Expansion with DRIFT
uε =
∞∑
i=0
εiui
(
t, x−b∗t
ε,x
ε
)
(2)
vε =∞∑
i=0
εivi
(
t, x−b∗t
ε,x
ε
)
(3)
Where b∗ is the drift which shall be computed along the process.Consider y = x
ε. Then we have:
∂
∂t
[
φ
(
t, x−b∗t
ε,x
ε
)]
=
∂φ
∂t−
n∑
j=1
b∗j
ε
∂φ
∂xj
(
t, x−b∗t
ε,x
ε
)
∂
∂xj
[
φ
(
t, x−b∗t
ε,x
ε
)]
=
[
∂
∂xjφ+
1
ε
∂
∂yjφ
](
t, x−b∗t
ε,x
ε
)
(4)
∀j ∈ 1, · · · , n
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Fredholm type result
Before listing the cascade of equations, we shall state a Fredholm typeresult that helps us solve them.
Lemma 2 For f ∈ L2(Y 0), g ∈ L2(∂Σ0) and h ∈ L2(∂Σ0), the followingsystem of p.d.e.’s admit a solution (u, v) ∈ H1
per(Y0)×H1(∂Σ0), unique up
to the addition of a constant multiple of (1,K),
b(y) · ∇yu− divy(D(y)∇yu) = f in Y 0,
−D(y)∇yu · γ + g = k(
u− 1
Kv)
on ∂Σ0,
bS(y) · ∇Sy v0 −DSdivSy (D
S(y)∇Sy v0)− h = k
(
u− 1
Kv)
on ∂Σ0,
y → (u(y), v(y)) Y − periodic,(5)
if and only if∫
Y0
f dy +
∫
∂Σ0
(g + h) dσ(y) = 0 (6)
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Cascade of Systems
Co-efficients of ε−2
b(y) · ∇yu0 − divy(D(y)∇yu0) = 0 in Y 0,
−D∇yu0 · γ = bS(y) · ∇Sy v0 −DSdivSy (D
S(y)∇Sy v0)
= k[
u0 −1
Kv0]
on ∂Σ0,
y → (u0(y), v0(y)) Y − periodic,(7)
The compatibilty condition is trivially satisfied.
Hence the existence and uniqueness of (u0, v0).
Substituting the test functions by (u0, v0) in the variational formulation of(7), we can deduce that
v0 = Ku0 and u0 = u0(t, x)
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Cascade of Systems Contd.
Co-efficients of ε−1
−b∗ · ∇xu0 + b(y) · (∇xu0 +∇yu1)− divy(D(y)(∇xu0 +∇yu1)) = 0 inY 0,
−b∗ · ∇xv0 + bS(y) · (∇Sxv0 +∇S
y v1)− divSy (DS(y)(∇S
xv0 +∇Sy v1))
= −D(y)(∇xu0 +∇yu1) · γ = k[
u1 −v1K
]
on∂Σ0,
y → (u1(y), v1(y)) Y − periodic,(8)
The linearity helps us deduce that
u1(t, x, y) = χ(y) · ∇xu0
andv1(t, x, y) = ω(y) · ∇xu0
The above representation of (u1, v1) results in the following coupled cellproblem, for i ∈ 1, · · · , n
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Cell Problem
b(y) · ∇yχi − divy(D(y)(∇yχi + ei)) = (b∗ − b(y)) · ei in Y 0,
bS(y) · ∇Syωi − divSy (D
S(y)(∇Syωi +Kei))
= K(b∗ − bS(y)) · ei + κ(
χi −1
Kωi
)
on ∂Σ0,
−D(y)(∇yχi + ei) · γ = κ(
χi −1
Kωi
)
on ∂Σ0,
y → (χi(y), ωi(y)) Y − periodic,(9)
Using the Fredholm result, we get the existence of (χi, ωi) provided
b∗ =
∫
Y 0
b(y) dy +K∫
∂Σ0
bS(y) dσ(y)
|Y 0|+K|∂Σ0|n−1
(10)
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Cascade of Systems contd.
Co-efficients of ε0
∂tu0 − b∗ · ∇xu1 + b(y) · (∇xu1 +∇yu2)
−divx(D(y)(∇xu0 +∇yu1))− divy(D(y)(∇xu1 +∇yu2)) = 0 in Y 0,
∂tv0 − b∗ · ∇xv1 + bS(y) · (∇Sxu1 +∇S
y u2)
−divx(GDS(y)(G∇xv0 +∇Sy v1))− divSy (D
S(y)(G∇xv1 +∇Sy v2))
= −D(y)(∇yu2 +∇xu1) · γ = κ[
u2 −1
Kv2]
on ∂Σ0,
y → (u2(y), v2(y)) Y − periodic,(11)
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Homogenized equation
The compatibility condition for (u2, v2) yields the homogenized equation.
Kd ∂tu0 = divx (A∗∇xu0) in (0, T )× R
n
Kd u0(0, x) = |Y 0|u0(x) + |∂Σ0|n−1v0(x), x ∈ R
n
(12)
Where, Kd = |Y 0|+K|∂Σ0|n−1, the dispersion tensor A∗ is given by
A∗
ij =
∫
Y 0
D (∇yχi + ei) · (∇yχj + ej) dy
+κ
∫
∂Σ0
(
χi −K−1ωi
) (
χj −K−1ωj
)
dσ(y)
+K
∫
∂Σ0
DS(
Gei +K−1∇Syωi
)
·(
Gej +K−1∇Syωj
)
dσ(y)
(13)
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Homogenized equation
The compatibility condition for (u2, v2) yields the homogenized equation.
Kd ∂tu0 = divx (A∗∇xu0) in (0, T )× R
n
Kd u0(0, x) = |Y 0|u0(x) + |∂Σ0|n−1v0(x), x ∈ R
n
(12)
Where, Kd = |Y 0|+K|∂Σ0|n−1, the dispersion tensor A∗ is given by
A∗
ij =
∫
Y 0
D (∇yχi + ei) · (∇yχj + ej) dy
+κ
∫
∂Σ0
(
χi −K−1ωi
) (
χj −K−1ωj
)
dσ(y)
+K
∫
∂Σ0
DS(
Gei +K−1∇Syωi
)
·(
Gej +K−1∇Syωj
)
dσ(y)
(13)
It should be noted that we have used the information we know of (u1, v1)in terms of (χ, ω). A∗ is symmetrized as anti-symmetric part doesn’tcontribute.
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Equivalent homogenized equation
Define uε(t, x) = u0(t, x− b∗
εt). Then, it is solution of
∂tuε +1
εb∗ · ∇uε = Kd
−1divx (A∗∇xuε) in (0, T )× R
n
Kd uε(0, x) = |Y 0|u0(x) + |∂Σ0|n−1v0(x), x ∈ R
n
(14)
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Numerical Study using FreeFem++
Numerical tests were done using FreeFem++.
Using Lagrange P1 finite elements.
Number of vertices = 23894.
The solid obstacles are isolated circular disks of radius 0.2
The velocity field b(y) is generated by solving the following filtrationproblem in the fluid part Y 0 of the unit cell Y . For simplicity, we have takenthe surface convection bS to be zero.
∇yp−∆yb = ei in Y 0,
divyb = 0 in Y 0,
b = 0 on ∂Σ0,
p, b Y 0 − periodic
(15)
Calculations were done to see the effect of the variation in κ and DS onthe effective co-efficients. They are seen to show a stable asymptoticbehaviour.
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Behavior of the cell solution
IsoValue-0.118263-0.101224-0.0898652-0.0785062-0.0671471-0.0557881-0.0444291-0.03307-0.021711-0.0103520.001007060.01236610.02372510.03508420.04644320.05780220.06916120.08052030.09187930.120277
IsoValue-0.0166337-0.0141745-0.0125351-0.0108956-0.00925613-0.00761666-0.0059772-0.00433773-0.00269826-0.001058790.0005806720.002220140.003859610.005499070.007138540.008778010.01041750.01205690.01369640.0177951
Figure 1: The cell solution χ1: Left, reference value κ = κ0; Right, κ = 5κ0
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Behavior of the cell solution contd.
IsoValue-0.00424724-0.00367644-0.0032959-0.00291537-0.00253483-0.0021543-0.00177377-0.00139323-0.0010127-0.000632165-0.0002516320.0001289020.0005094360.000889970.00127050.001651040.002031570.00241210.002792640.00374397
IsoValue-0.0181629-0.0155051-0.0137331-0.0119612-0.0101893-0.0084174-0.00664549-0.00487357-0.00310166-0.001329750.0004421670.002214080.003985990.005757910.007529820.009301730.01107360.01284560.01461750.0190473
Figure 2: The cell solution χ1: Left, κ = 6κ0; Right, κ = 8κ0
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Behavior of logitudinal dispersion with variation in react ion rate
0
50
100
150
200
250
0 1e-05 2e-05 3e-05 4e-05 5e-05 6e-05 7e-05 8e-05 9e-05 0.0001
"plotASTAR11ktille-4.dat" using 1:2
1.45
1.5
1.55
1.6
1.65
1.7
1.75
1.8
0 5 10 15 20 25 30 35 40 45 50
"plotASTAR11kbw1and50.dat" using 1:2
Figure 3: The variation of effective longitudinal diffusion: Left, κ tending to0; Right, κ increasing in magnitude
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Behavior of transverse dispersion with variation in reacti on rate
0.198
0.199
0.2
0.201
0.202
0.203
0.204
0.205
0.206
0 1e-05 2e-05 3e-05 4e-05 5e-05 6e-05 7e-05 8e-05 9e-05 0.0001
"plotASTAR22ktille-4.dat" using 1:2
0.25
0.3
0.35
0.4
0.45
0.5
0.55
0.6
0 5 10 15 20 25 30 35 40 45 50
"plotASTAR22kbw1and50.dat" using 1:2
Figure 4: The variation of effective transverse diffusion: Left, κ tending to0; Right, κ increasing in magnitude
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Behavior of effective dispersion with variation in surface diffusion
0.828
0.83
0.832
0.834
0.836
0.838
0.84
0.842
0.844
0.846
0 1 2 3 4 5 6 7 8 9 10
"plotASTAR11.dat" using 1:2
0.826
0.828
0.83
0.832
0.834
0.836
0.838
0.84
0.842
0.844
0.846
0 1 2 3 4 5 6 7 8 9 10
"plotASTAR22.dat" using 1:2
Figure 5: The variation of effective diffusion with DS increasing in magni-tude: Left, longitudinal diffusion; Right, transverse diffusion
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Conclusions
• Study of the effective behaviour of the model with the variation in thereaction rate κ.
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Conclusions
• Study of the effective behaviour of the model with the variation in thereaction rate κ. The ill-posedness of the cell problems result in theblow-up of the effective tensor when κ → 0.
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Conclusions
• Study of the effective behaviour of the model with the variation in thereaction rate κ. The ill-posedness of the cell problems result in theblow-up of the effective tensor when κ → 0. When κ → ∞, thetransverse and longitudinal dispersion exhibit a stable asymptoticbehaviour with transverse dispersion remaining relatively less oncomparison with longitudinal dispersion.
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Conclusions
• Study of the effective behaviour of the model with the variation in thereaction rate κ. The ill-posedness of the cell problems result in theblow-up of the effective tensor when κ → 0. When κ → ∞, thetransverse and longitudinal dispersion exhibit a stable asymptoticbehaviour with transverse dispersion remaining relatively less oncomparison with longitudinal dispersion.
• Study of the effective behaviour of the model with the variation in thesurface diffusion DS .
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Conclusions
• Study of the effective behaviour of the model with the variation in thereaction rate κ. The ill-posedness of the cell problems result in theblow-up of the effective tensor when κ → 0. When κ → ∞, thetransverse and longitudinal dispersion exhibit a stable asymptoticbehaviour with transverse dispersion remaining relatively less oncomparison with longitudinal dispersion.
• Study of the effective behaviour of the model with the variation in thesurface diffusion DS . The case DS = 0 exactly matches with theprevious results on effective dispersion with no surface diffusion.
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Conclusions
• Study of the effective behaviour of the model with the variation in thereaction rate κ. The ill-posedness of the cell problems result in theblow-up of the effective tensor when κ → 0. When κ → ∞, thetransverse and longitudinal dispersion exhibit a stable asymptoticbehaviour with transverse dispersion remaining relatively less oncomparison with longitudinal dispersion.
• Study of the effective behaviour of the model with the variation in thesurface diffusion DS . The case DS = 0 exactly matches with theprevious results on effective dispersion with no surface diffusion.When DS → ∞, the transverse and longitudinal dispersion exhibit astable asymptotic behaviour with transverse dispersion remainingalmost equal to longitudinal dispersion.
![Page 43: Homogenization of reactive flows in porous media · 2012-10-15 · Homogenization of reactive flows in porous media G. Allaire ∗, H. Hutridurga ∗ 13-October-2010 ∗Centre de](https://reader035.fdocuments.us/reader035/viewer/2022062603/5f0f525d7e708231d4439580/html5/thumbnails/43.jpg)
Conclusions
• Study of the effective behaviour of the model with the variation in thereaction rate κ. The ill-posedness of the cell problems result in theblow-up of the effective tensor when κ → 0. When κ → ∞, thetransverse and longitudinal dispersion exhibit a stable asymptoticbehaviour with transverse dispersion remaining relatively less oncomparison with longitudinal dispersion.
• Study of the effective behaviour of the model with the variation in thesurface diffusion DS . The case DS = 0 exactly matches with theprevious results on effective dispersion with no surface diffusion.When DS → ∞, the transverse and longitudinal dispersion exhibit astable asymptotic behaviour with transverse dispersion remainingalmost equal to longitudinal dispersion.
• The Mathematical justification of the upscaling using two-scaleconvergence with drift upon introducing 2-scale convergence withdrift on surfaces.
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References
[1] G. Allaire, R. Brizzi, A. Mikelic, A. Piatnitski, Two-scale expansion withdrift approach to the Taylor dispersion for reactive transport throughporous media, Chemical Engineering Science, 65, pp.2292-2300(2010)
[2] G. Allaire, A. Mikelic, A. Piatnitski, Homogenization approach to thedispersion theory for reactive transport through porous media, SIAM J.Math. Anal., 42, pp.125-144 (2010)
[3] H. Hutridurga, Master Thesis, Ecole Polytechnique (2010)
[4] E. Marusic-Paloka, A. Piatnitski, Homogenization of a nonlinearconvection-diffusion equation with rapidly oscillating coefficients andstrong convection, J. London Math. Soc., 72, pp.391-409 (2005)
[5] O. Pironneau, F. Hecht, A. Le Hyaric, FreeFem++ version 2.15-1,http://www.freefem.org/ff++/