1. Structural Design of Highway
Third Stage
Lecture 8
Lecture. Dr. Rana Amir Yousif
Highway and Transportation Engineering
Al-Mustansiriyah University
2017

2. References:
1. Nicholas J. Garber and Lester A. Hoel.”Traffic and Highway Engineering”, Fourth Edition.
2.Yoder; E. J. and M. W. Witczak, “Principles of Pavement Design”, A Wiley- Interscience Publication, John Wiley & Sons Inc., U.S.A., 1975.
3. Yaug H. Huang, “Pavement Analysis and Design”, Prentic Hall Inc., U.S.A., 1993.
4.“AASHTO Guide for Design of Pavement Structures 1993”, AASHTO, American Association of State Highway and Transportation Officials, U.S.A., 1993.
5. Oglesby Clarkson H., “Highway Engineering”, John Wiley & Sons Inc., U.S.A.,1975.

3. Correlations with Other Tests
Various empirical tests have been used to determine the material properties for pavement design . Most of these tests measure the strength of the material and are not a true representation of the resilient modulus. An extensive study was made by Van Til et al. (1972) to relate the resilient modulus and other test parameters to the soil support value or the layer coefficient employed in the AASHO design equation . These correlations can be used as a guide if other, more reliable, information is not available . It should be noted that any empirical correlation is based on a set of local conditions . The correlation is not valid if the actual conditions are different from those under which the correlation is established . Therefore, great care must be exercised in the judicious selection of the resilient modulus from these correlations.

4. Subgrade Soils Figure shows a correlation chart that can be used to estimate the resilient modulus of subgrade soils from the R value, CBR, Texas triaxial classification, and group index .
FIGURE Correlation chart for estimating resilient modulus of subgrade soils (1 psi = 6.9 kPa ) . (After Van Til et al. (1972) .

5. R Value:
The R value is the resistance value of a soil determined by a stabilometer. The stabilometer test was developed by the California Division of Highway sand measures basically the internal friction of the material ; the cohesion for bonded materials is measured by the cohesiometer test. Figure is a schematic diagram of stabilometer, which is a closed-system triaxial test. A vertical pressure of 160 psi (1.1MPa) is applied to a sample, 4 in . (102 mm) in diameter and about 4 .5 in. (114 mm) in height, and the resulting horizontal pressures induced in the fluid within the rubbe rmembrane are measured.

6. The resistance value is computed as
in which R is the resistance value ; pv is the applied vertical pressure of 160 psi (1 .1 MPa); ph is the transmitted horizontal pressure at p.S, of 160 psi (1 .1 MPa) ; and D2 is the displacement of stabilometer fluid necessary to increase horizontal pressure from 5 to 100 psi (35 to 690 kPa), measured in revolutions of a calibrated pump handle . The value of D2 is determined after the maximum vertical pressure of 160 psi (1 .1 MPa) is applied . If the sample is a liquid with no shear resistance, then ph = pv, or from Eq , R = 0. If the sample is rigid with no deformation at all, then ph = 0, or R = Therefore, the R value ranges from 0 to 100. To ensure that the sample is saturated, California used an
exudation pressure of 240 psi (1 .7 MPa), whereas Washington used 300 psi (2.1 MPa) .

7. CBR
The California Bearing Ratio test (CBR) is a penetration test, wherein a standard piston, having an area of 3 in . 2 (1935 mm2 ), is used to penetrate the soil at a standard rate of in . (1 .3 mm) per minute . The pressure at each 0 .1-in . (2.5-mm) penetration up to 0 .5 in . (12 .7 mm) is recorded and its ratio to the bearing value of a standard crushed rock is termed as the CBR. The standard values of a high-quality crushed rock are as follows :

8. Group Index Other Correlations
The group index, which ranges from 0 to 20, is used in the AASHTO soil classification system . The values vary with the percentage passing through a No. 200 sieve, the plasticity index, and the liquid limit and can be found from charts or formulas.
Other Correlations
In addition to Figure 7 .10, other correlations between MR, CBR, and R values are also available . These correlations could be quite different from those shown in Figure

9. in which MR is the resilient modulus in psi
in which MR is the resilient modulus in psi . The coefficient, 1500, could vary from 750 to 3000, with a factor of 2. Available data indicate that Eq provides better results at values of CBR less than about 20. In other words, the correlation appears to be more reasonable for fine-grained soils and fine sands than for granular materials. The Asphalt Institute (1982) proposed the following correlation between MR and the R value : Laboratory data obtained from six different soil samples were used by the Asphalt Institute (1982) to illustrate the relationships, as shown in Table The R values were obtained at an exudation pressure of 240 psi (1 .7 MPa). The CBR samples were compacted at optimum moisture content to maximum density and soaked before testing . The repeated load triaxial tests were performed at optimum conditions using a deviator stress of 6 psi (41 kPa) and a confining pressure of 2 psi (14 kPa) . It can be seen from Table 7 .4 that the equations for estimating MR from CBR and R values have a very limited range . The resilient moduli estimated from CBR values of 5.2 and 7 .6 and R values of 18 and 21 generally conform to the guidelines for accuracy within a factor of 2. Estimates from CBR values of 25 or higher and R values above 60 would appear to overestimate MR by Eqs and 7.7. It should be noted that the MR of granular materials increases with the increase in confining pressure, and that of fine-grained soils decreases with the increase in deviator stress . Therefore, a large variety of correlations might be obtained, depending on the confining pressure or the deviator stress to be used in the resilient modulus test .

10. Hot Mix Asphalt
Figure shows the relationships of the layer coefficient , Marshall stability, cohesiometer values, and resilient modulus .

11. Structural Layer Coefficient
In the AASHTO design method, the quality of the HMA, base, and subbase is indicated by their structural layer coefficients. These correlation charts were originally developed to determine the layer coefficients, but can also be used to determine the resilient modulus. More about layer coefficients is presented in Section
Example 7.4:
Given CBR values of 30 and 80, determine the corresponding R value, Texas classification, and resilient modulus when the materials are used as a base course, a subbase course, and a subgrade.
Solution: The correlations for base, subbase, and subgrade can be obtained from Figures 7 .15a , , and The results are tabulated in Table It can be seen from Table 7 .5 that the correlations among CBR, R value, and Texas classification are practically the same no matter whether the material is used as a base, a subbase, or a subgrade . This is not true for the resilient modulus, where a large variation exists. This is reasonable, because the resilient modulus depends on the state of stresses, which varies with the location where the material is to be placed .