Estimation of Resilient Modulus of Unbound Aggregates Using Performance-Related Base Course Properties Academic Article uri icon


  • 2014 American Society of Civil Engineers. This study aims at developing an accurate and efficient methodology to estimate the resilient modulus of unbound aggregates. First, a new resilient modulus model is proposed to incorporate the moisture dependence of the resilient modulus in addition to the stress dependence in existing models. Second, prediction models are developed to conveniently and accurately determine the coefficients in the proposed model. In order to characterize the moisture dependence of unbound aggregates, the degree of saturation and the matric suction parameter are added into the proposed model. The soil-water characteristic curve (SWCC) is used to determine the matric suction value at any given moisture content. The moisture dependence of the model is validated for selected materials with different moisture contents. In order to develop prediction models for the coefficients in the proposed model, laboratory experiments and multiple regression analysis are conducted on 20 different base course materials. The laboratory experiments include the improved repeated load triaxial test and tests to measure performance-related base course properties. A new test protocol is developed for the improved repeated load triaxial test, which is better adapted to the stress state of the base course under the actual traffic load than the current test protocols. A series of repeatable and performance-related base course properties are measured and used to develop the prediction models based on multiple regression analysis. These newly proposed properties include methylene blue value (MBV), percent fines content (pfc), gradation of particle sizes, and shape, angularity, and texture of aggregates. The developed prediction models have higher R-squared values than those using other base course properties.

published proceedings


author list (cited authors)

  • Gu, F., Sahin, H., Luo, X., Luo, R., & Lytton, R. L.

citation count

  • 90

complete list of authors

  • Gu, Fan||Sahin, Hakan||Luo, Xue||Luo, Rong||Lytton, Robert L

publication date

  • June 2015