Rapid estimation of resilient modulus of subgrade soils using performance-related soil properties

ABSTRACT

This study aims at developing an efficient and accurate methodology to estimate the resilient modulus of subgrade soils. First, a new resilient modulus model incorporating stress dependence and moisture dependence was proposed. Second, prediction models were developed to conveniently and accurately determine model parameters of SWCC and resilient modulus model. In order to characterise the moisture dependence of subgrade soils, the matric suction was added into the proposed model. The matric suction was measured by the pressure plate test and the soil-water characteristic curve (SWCC) was used to determine the matric suction value at any given moisture contents. In order to develop prediction models for model parameters of SWCC and resilient modulus model, the laboratory experiments and multiple regression analysis were conducted on 22 soil samples. A series of performance-related soil properties were measured and used to develop the coefficients prediction models. The developed coefficients prediction models using the performance-related soil properties have high R-squared values and were validated by comparing the measured and predicted values of resilient modulus. Therefore, when the basic physical properties of soils were obtained, the resilient modulus can be predicted for the subgrade soils at any given matric suctions and stress states.

KEYWORDS:

• Resilient modulus
• subgrade soils
• soil properties
• multiple regression analysis
• repeated load triaxial test

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by National Natural Science Foundation of China: [grant numbers 5181102194,51838001,51878070,51878078]; Excellent Youth Foundation of Natural Science Foundation of Hunan Province: [grant number 2018JJ1026]; Hunan Provincial Innovation Foundation For Postgraduate: [grant number CX2018B529]; Open Fund of Engineering Research Center of Catastrophic Prophylaxis and Treatment of Road & Traffic Safety of Ministry of Education (Changsha University of Science & Technology): [grant number kfj170404]; Key Project of Education Department of Hunan Province: [grant number 17A008]; National Key Research and Development Program of China: [grant number 2017YFC0805307].