[235.1.3] One of the main goals in studying the microstructure of porous
media is to identify geometric observables that correlate
strongly with macroscopic physical transport properties.
[235.1.4] To achieve this it is not only necessary to evaluate
the geometric observables.
[235.1.5] One also needs to calculate the effective transport
properties exactly, in order to be able to correlate them
with geometrical and structural properties.
[235.1.6] Exact solutions are now becoming available
and this section reviews exact results obtained recently in cooperation
with J. Widjajakusuma [10, 65, 67].
[235.1.7] For the disordered potential problem, specified above in equations
(2) through (7), the effective macroscopic
transport parameter is defined by
![]() |
(68) |
where the brackets denote an ensemble average over the
disorder defined in (25).
[235.1.8] The value of can be computed numerically
[66, 33].
[235.1.9] For the following results the material parameters
were chosen as
![]() |
(69) |
[235.1.10] Thus in the usual language of transport problems
the pore space is conducting while the matrix space
is chosen as nonconducting.
[235.1.11] Equations (2) through (7) need to be
supplemented with boundary conditions on the surface
of .
[235.1.12] A fixed potential gradient was applied between two
parallel faces of the cubic sample
, and
no-flow boundary condition were enforced on the
four remaining faces of
.
[235.2.1] The macroscopic effective transport properties
are known to show strong sample to sample
fluctuations.
[235.2.2] Because calculation of requires
a disorder average the four
microsctructures were subdivided into eight
octants of size
.
[235.2.3] For each octant three values of
were
obtained from the exact solution corresponding
to application of the potential gradient in
the
-,
- and
-direction.
[235.2.4] The values of
obtained from dividing the
measured current by the applied potential
gradient were then averaged.
[235.2.5] Table 3 collects the mean and the
standard deviation from these exact calculations.
[235.2.6] The standard
[page 236, §0]
deviations in Table 3 show that
the fluctuations in are indeed rather strong.
[236.0.1] If the system is ergodic then one expects that
can also be calculated from the exact solution
for the full sample.
[236.0.2] For sample EX the exact transport coefficient for the
full sample is
in the
-direction,
in the
-direction, and
in the
-direction [65].
[236.0.3] All of these are seen to fall within one standard
deviation of
.
[236.0.4] The numerical values have been confirmed
independently by [47].
[236.1.1] Finally it is interesting to observe that
seems to correlate strongly with
shown
in Figure 11.
[236.1.2] This result emphasizes the importance of non-Hadwiger
functionals because by construction there is no
relationship between
and porosity, specific
surface and correlation functions.
![]() |
![]() |
![]() |
![]() |
|
---|---|---|---|---|
![]() |
0.01880 | 0.01959 | 0.00234 | 0.00119 |
![]() |
![]() |
![]() |
![]() |
![]() |
[236.1.3] According to the general criteria discussed above in Section 3.1 a geometrical characterization of random media should be usable in approximate calculations of transport properties. [236.1.4] In practice the full threedimensional microstructure is usually not available in detail, and only approximate calculations can be made that are based on partial geometric knowledge.
[236.2.1] Local porosity theory [27, 28] was developed as a
generalized effective medium approximation for
that utilizes the partial geometric characterization
contained in the quantities
and
.
[236.2.2] It is therefore useful to compare the predictions
from local porosity theory with those from simpler
mean field approximations.
[236.2.3] The latter will be the
Clausius-Mossotti approximation with
as background phase
![]() |
(70) |
[page 237, §0]
the Clausius-Mossotti approximation with as background phase
![]() |
(71) |
and the self-consistent effective medium approximation [37, 35]
![]() |
(72) |
which leads to a quadratic equation for .
[237.0.1] The subscripts
and
in (71) and (70)
stand for "blocking" and "conducting".
[237.0.2] In all of these mean field approximations the porosity
is the only geometric observable representing
the influence of the microstructure.
[237.0.3] Thus two microstructures having the same porosity
are predicted to have the same transport parameter
.
[237.0.4] Conversely,
measurement of
combined with the knowledge of
allows to deduce the porosity from such formulae.
[237.1.1] If the microstructure is known to be homogeneous and isotropic with
bulk porosity , and if
, then the
rigorous bounds [24, 8, 62]
![]() |
(73) |
hold, where the upper and the lower bound are given by
the Clausius-Mossotti formulae, eqs. (71) and
(70).
[237.1.2] For the bounds are reversed.
[237.2.1] The proposed selfconsistent approximations for the effective transport coefficient of local porosity theory reads [27]
![]() |
(74) |
where and
are given in eqs. (71) and
(70).
[237.2.2] Note that (74) is still preliminary,
and a generalization is in preparation.
[237.2.3] A final form requires generalization to tensorial
percolation probabilities and transport parameters.
[237.2.4] Equation (74) is a generalization of the
effective medium approximation.
[237.2.5] In fact, it reduces to eq. (72) in the limit
.
[237.2.6] In the limit
it also reduces to eq. (72)
albeit with
in eq. (72) replaced with
.
[237.2.7] In both limits the basic assumptions underlying all effective
medium approaches become invalid.
[237.2.8] For small
the local geometries become strongly
correlated, and this is at variance with the basic
assumption of weak or no correlations.
[237.2.9] For large
on the other hand the assumption that
the local geometry is sufficiently simple becomes
invalid [27].
[237.2.10] Hence one expects that formula (74) will yield
good results only for intermediate
.
[237.2.11] The question which
to choose has been discussed
in the literature
[page 238, §0]
[12, 3, 10, 66, 33].
[238.0.1] For the results in Table 4 the so called percolation
length has been used which
is defined through the condition
![]() |
(75) |
assuming that it is unique.
[238.0.2] The idea behind this definition is that at the inflection
point the function changes most rapidly from its
trivial value
at small
to its equally
trivial value
at large
(assuming that the
pore space percolates).
The length
is typically larger than the
correlation length calculated from
[10, 11].
[238.1.1] The results obtained by the various mean field approximations
are collected in Table 4 [65, 67].
[238.1.2] The exact result is obtained by averaging the three values
for the full sample EX given in the previous section.
[238.1.3] The additional geometric information contained
in and
seems to give an improved
estimate for the transport coefficient.
![]() |
![]() |
![]() |
![]() |
![]() |
---|---|---|---|---|
0.094606 | 0.0 | 0.0 | 0.025115 | 0.020297 |