Table 6. Coefficients for hydraulic properties in the form of Gardner's
equations.
Moisture retention
Hydraulic conductivity
α
β
Material
Aw
AK
Subgrade
1171 (563)
0.01232
0.4760
0.1647
1.5905
1206 (565)
0.002399
0.7134
0.0005713
2.6395
1232 (566)
0.002260
0.6790
0.001885
1.8129
Class 3
Blended
0.026538
0.5933
0.0010507
3.5199
Stockpile
0.1735
0.3239
1647.1
0.7207
Class 4
6.59 105
Taxiway A
0.1520
0.2690
2.9620
aubbase
Class 5
Dense-graded
0.4961
0.3660
3.912
1.3930
stone
Class 6
1.0729 10 6
Blended
1.0001
0.4444
5.8979
We determined point values of θu and hp in the
Figure 8 shows the relationship between degree
moisture retention test and fitted eq 1 to the ex-
of saturation and hydraulic conductivity for the
traction curve using a least squares approach to
materials tested and for the substitute materials.
determine the best fitted parameters Aw and α.
Exponential regression curves fit to the data, which
Table 6 lists these parameters for the samples
include both extraction and absorption values, are
tested.
shown in Table 7.
Results of the hydraulic conductivity tests are
displayed vs. pore water tension in Figure 7. Again,
Table 7. Coefficients for hydraulic pro-
perties relating hydraulic conductivity
the dashed line in Figure 7 is the best fit approxi-
(k, cm/hr) to degree of saturation (S, %)
mation used in the model to represent the unsatur-
in the form k = A10 Β S.
ated hydraulic conductivity using the equation:
ks
Material
A
B
KH =
β
(2)
AK hp + 1
Subgrade
8.539 1021
1171 (563)
0.184
9.503 1022
1206 (565)
0.189
5.880 1020
1232 (566)
0.161
(cm/hr)
ks = saturated hydraulic conductivity (cm/
Class 3
3.035 1011
hr)
Blended
0.114
1.061 109
Stockpile
0.100
hp = pore pressure head (cm of water)
AK = Gardner's multiplier for hydraulic
Class 4
1.981 1010
conductivity
Taxiway A
0.103
β = Gardner's exponent for hydraulic
subbase
conductivity.
Class 5
8.3491 105
Dense-graded
0.050
We determined point values of KH and hp for
stone
each sample and fitted eq 2 to the extraction data
Class 6
using a least squares approach to determine the
1.063 104
Blended
0.056
best fitted parameters AK and β (Table 6).
14
Previous Page
