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Publication Number:
FHWAHRT12031
Date: August 2012 
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This model development served as both a validation and development of a new correlation using the LTPP database. The model form used was a power equation and can be expressed as follows:
Figure 68. Equation. Prediction model 12 for f_{t}.
Where:
f_{t} = Indirect tensile
strength of the PCC material.
f'c = Compressive strength of the mix determined at the same
age.
The model statistics are presented in table 23. The model was developed using 541 data points with an R^{2} value of 42.09 percent and an RMSE of 61 psi. Table 24 provides details of the range of data used to develop the model.
Table 23. Model statistics for tensile strength prediction model.
Parameter 
Estimate 
Standard Error 
95 Percent Confidence Limits 
Coefficient 
8.9068

2.0204

4.9381 to 12.8756

Power 
0.4785

0.0256

0.4282 to 0.5288

Table 24. Range of data used for tensile strength prediction model.
Parameter 
Minimum 
Maximum 
Average 
Compressive strength 
1,990 
12,360 
6,763 
Tensile strength 
316 
1,012 
600 
Figure 69 and figure 70 show the predicted versus measured plot and the residual errors plot, respectively. Figure 71 shows the sensitivity of the model to compressive strength. The relationship developed shows that for typical ranges of compressive strength (i.e., 3,000 to 6,000 psi), the PCC tensile strength varies from about 400 to 570 psi, which is a reasonable range for this strength parameter.
Figure 69. Graph. Predicted versus measured for tensile strength model.
Figure 70. Graph. Residual errors plot for tensile strength model.
Figure 71. Graph. Sensitivity of tensile strength prediction model to change compressive strength.
Topics: research, infrastructure, pavements and materials Keywords: research, infrastructure, pavements and materials, Pavements, LTPP, material properties, MEPDG, prediction model, Index properties TRT Terms: research, facilities, transportation, highway facilities, roads, parts of roads, pavements Updated: 10/15/2012
