set, had an R2 of 0.962 for 240 number of cases. Error analysis indi-

cated that 11 out of the 240 cases had errors exceeding 20 percent, and

these were cases with ti equal to 1.5 or 6.0 in. These were the

extremes of the range of ti used to develop Equation 4.21.

 When the data set was expanded to include tI and E4 values of 8.0

in. and 5.0 ksi, respectively, Equation 4.22 was obtained. This equa-

tion had an R2 of 0.953 for 400 number of observations. Error analysis

indicated that 30 out of 400 observations had predictive errors above 20

percent. These simulated pavements are listed in Table 4.11, which

shows that two pavements (numbers 24 and 28) had E2 predictions with 30

to 40 percent error. One pavement (number 27) had 54 percent prediction

error. When all three pavements with 30 percent or more predictive

errors were deleted from the data set, the R2 value increased from 0.953

to 0.956. This increase was considered not significant enough to war-

rant changing the Equation 4.22 format.

 The most interesting thing from Equation 4.22 was that most of the

errors occurred at the extreme limits of t, (1.5 and 8.0 in.). As shown

in Table 4.11, most of these high errors were pavements with E2 values

of 42.5 and 175.0 ksi. Predictions were generally good for intermediate

ti values, especially 4.5 and 6.0 in. Moreover, Equation 4.22 contains

sensor 8 deflection measurement (Ds) which is currently not made with

the conventional sensor array utilized by the FDOT. Therefore, the

reliability of this equation is contingent upon measurement of D8. In

the absence of D8 measurement, Equation 4.21 would be the best choice

for prediction of the base course modulus.

 4.4.2.3 Stabilized Subgrade Modulus, E3. Two equations were also

developed to predict E Equation 4.23 which holds for t1 values from