Abstract

The Utah Department of Transportation (UDOT) has fully implemented the Mechanistic-Empirical Pavement Design Guide for pavement design but has been using primarily level-three design inputs obtained from correlations to aggregate base materials developed at the national level. UDOT was interested in investigating correlations between laboratory measurements of resilient modulus, California bearing ratio (CBR), and other material properties specific to base materials commonly used in Utah; therefore, a statewide testing program was needed. The objectives of this research were to 1) determine the resilient modulus of several representative aggregate base materials in Utah and 2) investigate correlations between laboratory measurements of resilient modulus, CBR, and other properties of the tested materials. Two aggregate base materials were obtained from each of the four UDOT regions. Important material properties, including particle-size distribution, soil classification, and the moisture-density relationship, were investigated for each of the sampled aggregate base materials. The CBR and resilient modulus of each aggregate base material were determined in general accordance with American Society for Testing and Materials D1883 and American Association of State Highway and Transportation Officials T 307, respectively. After all of the data were collected, several existing models were evaluated to determine if one or more of them could be used to predict the resilient modulus values measured in this research. Statistical analyses were also performed to investigate correlations between measurements of resilient modulus, CBR, and other properties of the tested aggregate base materials, mainly including aspects of the particle-size distributions and moisture-density relationships. A set of independent predictor variables was analyzed using both stepwise regression and best subset analysis to develop a model for predicting resilient modulus. After a suitable model was developed, it was analyzed to determine the sensitivity of the model coefficients to the individual data points. For the aggregate base materials tested in this research, the average resilient modulus varied from 16.0 to 25.6 ksi. Regarding the correlation between resilient modulus and CBR, the test results show that resilient modulus and CBR are not correlated for the materials tested in this research. Therefore, a new model was developed to predict the resilient modulus based on the percent passing the No. 200 sieve, particle diameter corresponding to 30 percent finer, optimum moisture content, maximum dry density (MDD), and ratio of dry density to MDD. Although the equation may not be applicable for values outside the ranges of the predictor variables used to develop it, it is expected to provide UDOT with reasonable estimates of resilient modulus values for aggregate base materials similar to those tested in this research.

Degree

College and Department

Ira A. Fulton College of Engineering and Technology; Civil and Environmental Engineering

Rights

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