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45
Table 21. Coating test regression model results.
Bucket Mixer Pugmill Mixer
True T for 98% T for 89%
ID
Grade a b Coating a b Coating
°F (°C) °F (°C)
M 85.5-19.5 24590795 0.146 289 (143) 117 0.039 345 (174)
N 84.3-25.5 3518845 0.113 334 (168) 1911 0.053 361 (183)
G 82.5-24.2 146 0.051 347 (175) 8990 0.067 333 (167)
H 78.3-26.1 14 0.031 412 (211) 3183 0.064 318 (159)
C 75.1-38.7 30688 0.078 360 (182) 876 0.055 324 (162)
I 71.8-29.2 134998 0.112 284 (140) 130 0.042 333 (167)
B 69.3-37.3 3514 0.081 300 (149) 7 0.021 374 (190)
F 67.8-21.3 715 0.066 318 (159) 2902 0.068 298 (148)
O 65.6-29.7 404 0.056 347 (175) 130 0.044 318 (159)
K 65.3-13.0 58144 0.102 293 (175) 4 0.024 297 (147)
J 64.3-20.7 131832 0.107 295 (146) 2 0.017 318 (159)
E 60.9-33.1 9177 0.091 289 (143) 0.4 0.010 222 (106)
D 60.3-31.7 182 0.063 293 (145) 2 0.023 250 (121)
where C is the percentage coating at any temperature T, and Mixture Coating Tests with Incompletely
a and b are regression constants. Regression results for each Dried Aggregate
binder are summarized in Table 21. The relationships were used
A second small coating experiment was conducted to
to estimate the coating percentage of the binders at any temper-
assess the effect of residual aggregate moisture on the coating
ature. The equiviscous mixing temperatures for the unmodified
of the aggregates with four binders. One of the challenges
binders were used to establish reference coating percentages
with this limited experiment was preparing the samples with
for the bucket mixer and the pugmill mixers. These reference
residual moisture to specific mixing temperatures. The gran-
coating percentages were 98% (bucket) and 89% (pugmill
ite aggregate used in this experiment had a low water absorp-
mixer). The temperatures to achieve these coating percent-
tion (0.7%) and although the coarse aggregates were saturated
ages for each binder were then estimated with the Sigmoid
at the start of the final heating step by combining with hot, dry
function regression equations. These predicted mixing tem-
fine aggregate and using a blow torch, the amount of moisture
peratures for equivalent coating are included in Table 21.
remaining in the aggregate at the time the asphalt was added
It is evident from these results that the predicted tempera-
had certainly decreased substantially.
tures from the two laboratory mixers are different and neither
A paired t-test was used to compare the results of the coating
consistently provides reasonable mixing temperatures. With
test with and without incompletely dried aggregates. The exper-
the bucket mixer, the temperature to achieve the baseline
imental hypothesis was that the coating percentages were the
coating percentage for Binder H was 412°F (211°C). This
same (difference = 0) for partially wet and dry aggregates. The
result is much higher than most asphalt technologists con-
results, provided in Table 22, show that there is a high prob-
sider reasonable. At the other extreme, the lowest predicted
ability (P-value = 0.469) that the coating percentages of dry
temperature to achieve the baseline coating percentage was
samples and incompletely dry samples were not statistically
for Binder I, which is not consistent with the rank of the
different. Some asphalt technologists have suggested that
binder grades. Binder M, modified with SBS and SasobitŪ, is
somewhat lower than the other highly modified binders, but
Table 22. Results of paired T-test for %coating
this may be due to the beneficial effect of the Fischer Tropsch
using wet and dry aggregates.
wax. For the pugmill mixer, the predicted temperature for
modified Binder B is excessive, and the temperatures for Paired T for Wet %Coated - Dry %Coated
the lowest-graded binders, D and E, are lower than expected. N Mean St Dev SE Mean
Wet %Coated 32 66.0219 27.8339 4.9204
Overall, the inconsistent coating test results for several binders
Dry %Coated 32 63.0844 31.3435 5.5408
demonstrate the challenge of using this method to predict Difference 32 2.93750 22.66805 4.00718
mixing temperatures and to use this approach to validate the
95% CI for mean difference: (5.23520, 11.11020)
candidate methods. T-Test of mean difference = 0 (vs not = 0): T-Value = 0.73 P-Value = 0.469
