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Federal Highway Administration Research and Technology
Coordinating, Developing, and Delivering Highway Transportation Innovations
REPORT |
This report is an archived publication and may contain dated technical, contact, and link information |
Publication Number: FHWA-HRT-12-030 Date: August 2012 |
Publication Number:
FHWA-HRT-12-030
Date: August 2012 |
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This model was developed to estimate the long-term strength of cores taken from a pavement. Data from only the GPS sections were utilized, and they included sections greater than 5 years in age. Strength data at multiple ages were available on some of the sections. A preliminary analysis indicated that pavement age was not a significant factor in the model. In other words, for pavements that have been in service for several years, the strength was more a function of its material parameters than age. This suggests that strength gain is relatively minimal after 5 years or is not noticed in a statistical sense. It then becomes reasonable, or perhaps even necessary, from a statistical standpoint to average the strengths for each section.
The model selected for the long-term strength can be expressed as follows:
Where:
f_{c, LT} = Long-term compressive strength, psi.
CMC = Cementitious materials content, lb/yd^{3}.
uw = Unit weight, lb/ft^{3}.
The regression statistics for this model are presented in table 30. The model was developed using 201 data points, and the prediction has an R^{2} value of 18 percent and an RMSE value of 1,179 psi. Table 31 provides details of the range of data used to develop the model. Figure 162 and figure 163 show the predicted versus measured plot and the residual plot, respectively. From observing figure 162, it is evident that this model does not have a good predictive ability, and while there is no significant bias, the error in prediction is fairly high (see figure 163). This model needs to be used with caution, and other means to verify the value would be necessary, such as core tests.
Variable |
DF |
Estimate |
Standard Error |
t-Value |
P_{r} > |t| |
VIF |
Intercept |
1 |
-3,467.3508 |
1,720.49637 |
-2.02 |
0.0452 |
0 |
Cementitious |
1 |
3.63452 |
1.38354 |
2.63 |
0.0093 |
1.024 |
(Unit weight)^{2} |
1 |
0.42362 |
0.06634 |
6.39 |
< 0.0001 |
1.024 |
The mode statistics for table 30 are as follows:
Parameter |
Minimum |
Maximum |
Average |
Cementitious content |
354 |
781 |
550 |
Unit weight |
134 |
156 |
147 |
Compressive strength |
4,315 |
11,750 |
7,655 |
The compressive strength models presented in this section reproduce the trends present in the datasets used for each correlation. It is highly recommended that a user estimate the strength based on as many models as possible with the information available at the time of analysis. This might provide a fair assessment of the ranges of compressive strength likely for the project and at different ages.
This section presents a comparison of the various models, and the graphs used for this discussion also include raw data plotted with the various relationships. Figure 164 through figure 168 show the relationship between compressive strength and CMC, w/c ratio, and unit weight, respectively. Figure 167 and figure 168 show the strength gain at short- and long-term ages, respectively.
Note that relationships have been plotted for typical values for all variables, and the raw data used in the models do not necessarily lie on the plots.
The following observations can be made:
These observations illustrate the benefit of comparing predictions made by the various models available to obtain the range of strength that each project or observation could develop. Any other information to substantiate or validate the strength predictions should be utilized whenever possible, such as strength values from other projects that have used similar materials and mix design.