Progress and Prospect of the Prediction Model of the Resilient Modulus of Subgrade Soils

The resilient modulus of the subgrade is a fundamental parameter for flexible pavement design. Therefore, the prediction of the resilient modulus of subgrade soils, MR, is the basis for determining the resilient modulus of the subgrade. Here, the resilient modulus prediction models of subgrade soils proposed in the literature were reviewed and the models were summarized into three groups according to the model variables: Group A, the constitutive models were built with stress states; Group B, the constitutive models incorporated the matric suction into applied shearing or confining stresses; and Group C, the constitutive models expounded the independent stress state variable approach. Two equations selected from each of the groups were used to predict the resilient modulus for three compacted subgrade soils. The results indicate that the models of Group A are simple in form, considering the effects of stress variables such as bulk stress, deviatoric stress, and octahedral shear stress, but the reflection of the subgrade humidity state is only reflected in the regression coefficients (k1, k2, k3). Models of Group B were based on the micro-mechanical theory and the laws of thermodynamics or the Bishop effective stress principle based on unsaturated soil. Experimental determination of the effective stress parameters is costly and challenging, while determination of these parameters an empirical formula will result in a significant error. Models of Group C were characterized as forms of increment and product. The incremental form does not consider the influence of matric suction affected by the confining pressure and deviatoric stress. Therefore, adopting the product form for coupled matric suction was suggested. In order to propose the subgrade soil resilient modulus prediction model suitable for China's subgrade pavement design system, further research should be carried out in terms of the loading sequence, matric suction test, prediction model building, and the dry and wet cycles. © 2020, Editorial Department of China Journal of Highway and Transport. All right reserved.