Abstract
The resilient modulus of the materials used in various pavement layers has been used extensively as an important material property in structural design of pavement. The state of stress and moisture content of cohesive soils have been observed to exert significant effects on the measured resilient modulus. Since the moisture content in the cohesive subgrade soils underneath the pavement undergoes seasonal changes due to infiltration of precipitations and since characterization of moisture and stress dependent resilient modulus of cohesive soils is a demanding and tedious task, there is a practical need for a predictive equation for the resilient modulus as a function of stress states and moisture content. This paper presents a new predictive equation for the resilient modulus of cohesive soils using the concept of soil suction. The accuracy of the proposed model is validated against experimental data of A-4 and A-6 soils conducted by the writers as well as by other data available in the literature. The proposed model provides advantages over the existing predictive equations by reducing the number of tests and soil specimens needed for determining the regression coefficients in the equation. The proposed predictive equation compares well with the empirical equation in the new mechanistic empirical pavement design guide (MEPDG) in predicting the effect of moisture content variation on the resilient modulus. The proposed model provides an advantage over the MEPDG empirical equation in taking into account the effects of both the stress state and moisture content on the resilient modulus of cohesive soils.